spendergast Informed Prostate Cancer Patient: September 2016

Wiley: Radar Data Processing With Applications - He You, Xiu Jianjuan, Guan Xin

Radar Data Processing with Applications

Description

A systematic introduction to the theory, development and latest research results of radar data processing technology

Presents both classical theory and development methods of radar data processing
Provides state-of-the-art research results, including data processing for modern style radars, and tracking performance evaluation theory
Includes coverage of performance evaluation, registration algorithm for Radar network, data processing of passive radar, pulse Doppler radar, and phased array radar
Has applications for those engaged in information engineering, radar engineering, electronic countermeasures, infrared techniques, sonar techniques, and military command

About the Authors xiv
Preface xvi
1 Introduction 1

1.1 Aim and Significance of Radar Data Processing 1
1.2 Basic Concepts in Radar Data Processing 2
1.3 Design Requirements and Main Technical Indexes of Radar Data Processors 9
1.4 History and Present Situation of Research in Radar Data Processing Technology 12
1.5 Scope and Outline of the Book 14

2 Parameter Estimation 20

2.1 Introduction 20
2.2 The Concept of Parameter Estimation 20
2.3 Four Basic Parameter Estimation Techniques 23
2.4 Properties of Estimators 26
2.5 Parameter Estimation of Static Vectors 28
2.6 Summary 33

3 Linear Filtering Approaches 34

3.1 Introduction 34
3.2 Kalman Filter 34
3.3 Steady-State Kalman Filter 48
3.4 Summary 52

4 Nonlinear Filtering Approaches 53

4.1 Introduction 53
4.2 Extended Kalman Filter 53
4.3 Unscented Kalman Filter 58
4.4 Particle Filter 65
4.5 Summary 71

5 Measurement Preprocessing Techniques 72

5.1 Introduction 72
5.2 Time Registration 72
5.3 Space Registration 75
5.4 Radar Error Calibration Techniques 88
5.5 Data Compression Techniques 89
5.6 Summary 93

6 Track Initiation in Multi-target Tracking 95

6.1 Introduction 95
6.2 The Shape and Size of Track Initiation Gates 96
6.3 Track Initiation Algorithms 100
6.4 Comparison and Analysis of Track Initiation Algorithms 109
6.5 Discussion of Some Issues in Track Initiation 116
6.6 Summary 117

7 Maximum Likelihood Class Multi-target Data Association Methods 118

7.1 Introduction 118
7.2 Track-Splitting Algorithm 118
7.3 Joint Maximum Likelihood Algorithm 123
7.4 0–1 Integer Programming Algorithm 126
7.5 Generalized Correlation Algorithm 130
7.6 Summary 137

8 Bayesian Multi-target Data Association Approach 138

8.1 Introduction 138
8.2 Nearest-Neighbor Algorithm 138
8.3 Probabilistic Data Association Algorithm 141
8.4 Integrated Probabilistic Data Association Algorithm 152
8.5 Joint Probabilistic Data Association Algorithm 154
8.6 Summary 167

9 Tracking Maneuvering Targets 169

9.1 Introduction 169
9.2 Tracking Algorithm with Maneuver Detection 170
9.3 Adaptive Tracking Algorithm 174
9.4 Performance Comparison of Maneuvering Target Tracking Algorithms 189
9.5 Summary 201

10 Group Target Tracking 203

10.1 Introduction 203
10.2 Basic Methods for Track Initiation of the Group Target 204
10.3 The Gray Fine Track Initiation Algorithm for Group Targets 214
10.4 Centroid Group Tracking 233
10.5 Formation Group Tracking 238
10.6 Performance Analysis of Tracking Algorithms for Group Targets 240
10.7 Summary 246

11 Multi-target Track Termination Theory and Track Management 250

11.1 Introduction 250
11.2 Multi-target Track Termination Theory 250
11.3 Track Management 258
11.4 Summary 275

12 Passive Radar Data Processing 276

12.1 Introduction 276
12.2 Advantages of Passive Radars 276
12.3 Passive Radar Spatial Data Association 278
12.4 Optimal Deployment of Direction-Finding Location 289
12.5 Passive Location Based on TDOA Measurements 299
12.6 Summary 303

13 Pulse Doppler Radar Data Processing 304

13.1 Introduction 304
13.2 Overview of PD Radar Systems 304
13.3 Typical Algorithms of PD Radar Tracking 307
13.4 Performance Analysis on PD Radar Tracking Algorithms 321
13.5 Summary 331

14 Phased Array Radar Data Processing 332

14.1 Introduction 332
14.2 Characteristics and Major Indexes 333
14.3 Structure and Working Procedure 334
14.4 Data Processing 336
14.5 Performance Analysis of the Adaptive Sampling Period Algorithm 355
14.6 Summary 361

15 Radar Network Error Registration Algorithm 362

15.1 Introduction 362
15.2 The Composition and Influence of Systematic Errors 362
15.3 Fixed Radar Registration Algorithm 366
15.4 Mobile Radar Registration Algorithm 380
15.5 Summary 402

16 Radar Network Data Processing 405

16.1 Introduction 405
16.2 Performance Evaluation Indexes of Radar Networks 406
16.3 Data Processing of Monostatic Radar Networks 408
16.4 Data Processing of Bistatic Radar Networks 413
16.5 Data Processing of Multistatic Radar Networks 420
16.6 Track Association 423
16.7 Summary 426

17 Evaluation of Radar Data Processing Performance 427

17.1 Introduction 427
17.2 Basic Terms 428
17.3 Data Association Performance Evaluation 429
17.4 Performance Evaluation of Tracking 432
17.5 Evaluation of the Data Fusion Performance of Radar Networks 436
17.6 Methods of Evaluating Radar Data Processing Algorithms 438
17.7 Summary 440

18 Radar Data Processing Simulation Technology 441

18.1 Introduction 441
18.2 Basis of System Simulation Technology 442
18.3 Simulation of Radar Data Processing Algorithms 449
18.4 Simulation Examples of Algorithms 457
18.5 Summary 463

19 Practical Application of Radar Data Processing 464

19.1 Introduction 464
19.2 Application in ATC Systems 464
19.3 Application in Shipboard Navigation Radar 474
19.4 Application in Shipboard Radar Clutter Suppression 476
19.5 Application in Ground-Based Radar 480
19.6 Applications in Shipboard Monitoring System 482
19.7 Application in the Fleet Air Defense System 484
19.8 Applications in AEW Radar 486
19.9 Application in Air Warning Radar Network 492
19.10 Application in Phased Array Radar 495
19.11 Summary 498

20 Review, Suggestions, and Outlook 499

20.1 Introduction 499
20.2 Review of Research Achievements 499
20.3 Issues and Suggestions 502
20.4 Outlook for Research Direction 505

References 508
Index 523

Related/Background:

UC San Diego /Radar data processing with applications / You He, Jianjuan Xiu, Xin Guan
You He Bibliography
B. Jing, W. Guohong, X. Jianjuan and W. Xiaobo, "New deghosting method based on generalized triangulation," in Journal of Systems Engineering and Electronics, vol. 20, no. 3, pp. 504-511, June 2009.
Abstract: A new deghosting method based on the generalized triangulation is presented. First, two intersection points corresponding to the emitter position are obtained by utilizing two azimuth angles and two elevation angles from two jammed 3-D radars (or 2-D passive sensors). Then, hypothesis testing based deghosting method in the multiple target scenarios is proposed using the two intersection points. In order to analyze the performance of the proposed method, the correct association probability of the true targets and the incorrect association probability of the ghost targets are defined. Finally, the Monte Carlo simulations are given for the proposed method compared with the hinge angle method in the cases of both two and three radars. The simulation results show that the proposed method has better performance than the hinge angle method in three radars case.
keywords: {Earth;Position measurement;Radar measurements;Sensors;Testing;Vectors;deghosting;distributed radar network;generalized triangulation;hinge angle;hypothesis testing},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6074692&isnumber=6074677
Xiu Jianjuan, He You, Xiu Jianhua and Yan Hongxing, "Study on multitarget tracking algorithm in passive cross location systems," Radar, 2001 CIE International Conference on, Proceedings, Beijing, 2001, pp. 1119-1123.
doi: 10.1109/ICR.2001.984907
Abstract: When the coordinates of the target are obtained by direction-finding location through multiple passive sensors, the associated bearing measurements must be the same time detection of these sensors. But these sensors may have different sampling intervals, and the time of these sensors beginning to receive the target signal may be also different. In this case, the first problem one must solve in direction-finding location is measurement synchronization. The paper studies this problem and proposes a method to solve it. An improved least distance method is used in this paper to eliminate the false intersection points. The methods of track initiation and maintenance in multitarget tracking are also discussed in this paper. The simulation results show that passive sensors can track multiple targets at the same time using the methods discussed in this paper
keywords: {direction-of-arrival estimation;military radar;radar antennas;radar signal processing;radar tracking;signal sampling;synchronisation;target tracking;bearing measurements;direction-finding location;false intersection points;least distance method;measurement synchronization;multiple passive sensors;multitarget tracking;passive cross location systems;radar antennas;sampling intervals;time detection;track initiation;track maintenance;Aerospace engineering;Azimuth;Coordinate measuring machines;Extraterrestrial measurements;Goniometers;Helium;Navigation;Sampling methods;Target tracking;Time measurement},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=984907&isnumber=21220
Liu Xiaohua, Xiu Jianjuan and Wang Guohong, "Passive tracking algorithm of single sensor based on multi-hypothesis unscented Kalman filter," Radar Conference, 2009 IET International, Guilin, 2009, pp. 1-4.
doi: 10.1049/cp.2009.0403
Abstract: Considering that the motion targets are remarkably observable in the situation of bearing-only location with single sensor, a new method is presented in this paper, namely, passive tracking algorithm based on the multi-hypothesis unscented Kalman filter (UKF). The algorithm firstly divides the probable initial range interval of the target into subintervals, and for each subinterval UKF is used. Finally, the combined state estimate is obtained as weighted sums of the state estimate of each subinterval. Simulation proves that compared with other passive target motion analysis methods under the same circumstance, the method shows an apparently better performance, especially in target status accuracy and algorithm stability. Moreover, the method is advantaged for it doesn't call for single sensor measurement data, and it doesn't require the sensor platform to have particular maneuver.
keywords: {Kalman filters;military radar;passive radar;radar tracking;target tracking;bearing-only location;defense system;multihypothesis unscented Kalman filter;passive radar;passive target motion analysis method;passive target tracking algorithm;single sensor;state estimation;bearings-only;multi-hypothesis;passive location;unscented Kalman filter(UKF)},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5367416&isnumber=5367270
Xiu Jianjuan, He You, Xiu Jianhua and Wang Guohong, "Passive location algorithm of two sensors based on multihypothesis extended Kalman filter," Signal Processing, 2002 6th International Conference on, 2002, pp. 1411-1414 vol.2.
doi: 10.1109/ICOSP.2002.1180057
Abstract: Multitarget tracking with bearings only measurements of two passive sensors is a very important problem, which has not been solved. To counter this problem a method is proposed in this paper, This method firstly used the bearing measurements of two passive sensors to estimate the initial range interval of targets, which are divided into several subintervals. At each subinterval an extended Kalman filter and a multihypothesis method are used to estimate the state of targets. At the same time the bearing measurements are associated. Combined state estimate is obtained as weighted sums of the state estimate of each subinterval. Simulation results show that through using the algorithm discussed in this paper two passive sensors can locate and track multiple targets at the same time.
keywords: {Kalman filters;antenna arrays;array signal processing;military radar;radar antennas;radar tracking;receiving antennas;target tracking;bearings only measurements;combined state estimate;extended Kalman filter;multihypothesis extended Kalman filter;multihypothesis method;multitarget tracking;passive location algorithm;passive sensors;subinterval;Aerospace engineering;Auditory system;Counting circuits;Helium;Position measurement;Radar tracking;State estimation;Target tracking;Time measurement;Vehicles},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=1180057&isnumber=26504
He You, Wang Guohang, Xiu Jianjuan and Xiu Jianhua, "Redundant data compression and location accuracy analysis in T/R-R bistatic radar system," Signal Processing Proceedings, 2000. WCCC-ICSP 2000. 5th International Conference on, Beijing, 2000, pp. 1951-1955 vol.3.
doi: 10.1109/ICOSP.2000.893487
Abstract: In modern ECM and ECCM environments, bistatic radar systems have drawn increasing interest in military applications. Bistatic radar system involves two types: T-R and T/R-R. However, the feasibility of compressing redundant data in a bistatic radar system by Markov estimation has received little attention so far. This paper presents a theorem with respect to this particular issue. Theoretical analysis shows that, if there are same components in two measurement sets, redundant data compression in the sense of Markov estimation can not be made. Under the circumstance that the redundant data can be compressed, simulation results show that data compression can improve the location precision greatly in a bistatic radar system, and particularly in the region of the base line, the near region of the transmitter station and the receiver station
keywords: {Markov processes;data compression;military radar;parameter estimation;radar receivers;radar signal processing;radar transmitters;ECCM;ECM;Markov estimation;T/R-R bistatic radar system;base line region;bistatic radar system;location accuracy;military radar systems;receiver station;redundant data compression;simulation results;transmitter station;Aerospace engineering;Bistatic radar;Data compression;Electronic countermeasures;Equations;Helium;Least squares methods;Measurement errors;Radar scattering;Transmitters},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=893487&isnumber=19317
W. Guohong and H. You, "Sequential track monitoring with multiple 2-D Passive sensors," in Journal of Systems Engineering and Electronics, vol. 9, no. 2, pp. 31-39, June 1998.
Abstract: Track monitoring is a fast method of determining incorrect return-to-track and track-to-track assignments. An analytical method to evaluate the effectiveness of track monitoring was presented by reference [1]. In order to reduce the probability of initiating or accepting the ghost track, two sequential track monitoring algorithms, which use the inclination angles to form test statistics, are proposed in this paper. Two decision rules are given and the corresponding thresholds are derived. The paper also gives the estimation methods of the noncentral parameter of noncentral chi-square distribution when the true value of it is unknown. the algorithms can adaptively estimate the decision thresholds and can make sequential track monitoring decision on line. Simulation is also made and the results show that the proposed algorithms are effective and feasible.
keywords: {Equations;Helium;Monitoring;Probability;Sensor systems;Target tracking;Association;Inclination angle;Passive sensor;Track monitoring},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6075365&isnumber=6075356

H. You and G. Jian, "Performance analysis of two CFAR detectors in clutter edge situation," in Journal of Systems Engineering and Electronics, vol. 12, no. 2, pp. 44-51, June 2001.
Abstract: This paper studies the performance of the GOSGO and GOSSO CFAR detectors [1] in clutter edge situation. The authors derive the analytic expressions of the false alarm probabilities in that situation, analyze their performances against clutter edge, and compare them with the OS, CA, GO and SO detectors. The results show that GOSGO possesses better performance than GO for countering clutter, but the performance of GOSSO is very unideal.
keywords: {Clutter;Detectors;Equations;Estimation;Image edge detection;Nickel;Noise;CFAR detection;Clutter edge;Generalized modified order statistic},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6078161&isnumber=6078150

T. Xiaoming, H. You and W. Guohong, "A new deghosting algorithm with hypothesis testing data fusion," in Journal of Systems Engineering and Electronics, vol. 14, no. 2, pp. 14-19, June 2003.
Abstract: Eliminating the false intersection (deghosting) is a difficult problem in a passive cross location system. Using a decentralized decision fusion topology, a new deghosting algorithm derived from hypothesis testing theory is developed. It uses the difference between ghosts and true targets in the statistical error, which occurs between their projection angles on a deghosting sensor and is measured from a deghosting sensor, and constructs a corresponding test statistic. Under the Gaussian assumption, ghosts and true targets are decided and discriminated by Chi-square distribution. Simulation results show the feasibility of the algorithm.
keywords: {Estimation;Helium;Measurement uncertainty;Simulation;Testing;Topology;Vectors;Decentralized decision fusion;Deghosting;Hypothesis testing},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6077498&isnumber=6077492

H. You and X. Wei, "Relationship between track fusion solutions with and without feedback information," in Journal of Systems Engineering and Electronics, vol. 14, no. 2, pp. 47-51, June 2003.
Abstract: In distributed multisensor data fusion systems, there are two types of track fusion approaches. One is sensor track fusion with feedback information, the other is without feedback information. This paper proves that the solutions of sensor track fusion with and without feedback information are both optimal and equal.
keywords: {Educational institutions;Estimation;Helium;Noise;Radar tracking;Target tracking;Vectors;Data fusion;Feedback;Multisensor},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6077503&isnumber=6077492

M. Xiangwei, G. Jian and H. You, "Analysis of linear weighted order statistics CFAR algorithm," in Journal of Systems Engineering and Electronics, vol. 15, no. 3, pp. 232-236, Sept. 2004.
Abstract: CFAR technique is widely used in radar targets detection fields. Traditional algorithm is cell averaging (CA), which can give a good detection performance in a relatively ideal environment. Recently, censoring technique is adopted to make the detector perform robustly. Ordered statistic (OS) and trimmed mean (TM) methods are proposed. TM methods treat the reference samples which participate in clutter power estimates equally, but this processing will not realize the effective estimates of clutter power. Therefore, in this paper a quasi best weighted (QBW) order statistics algorithm is presented. In special cases, QBW reduces to CA and the censored mean level detector (CMLD).
keywords: {Algorithm design and analysis;Clutter;Detectors;Helium;Probability;Radar detection;CFAR;detection;order statistics;radar},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6071467&isnumber=6071462

Z. Li, H. You and Z. Weihua, "Study on data association algorithm of multi-passive-sensor location system," in Journal of Systems Engineering and Electronics, vol. 16, no. 3, pp. 489-493, Sept. 2005.
Abstract: Aiming at three-passive-sensor location system, a generalized 3-dimension (3-D) assignment model is constructed based on property information, and a multi-target programming model is proposed based on direction-finding and property fusion information. The multi-target programming model is transformed into a single target programming problem to resolve, and its data association result is compared with the results which are solved by using one kind of information only. Simulation experiments show the effectiveness of the multi-target programming algorithm with higher data association accuracy and less calculation.
keywords: {Accuracy;Data models;Helium;Mathematical model;Navigation;Programming;Sensors;cost matrix;data association;joint information;programming model},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6071190&isnumber=6071185

L. Hongsheng, H. You and Y. Rijie, "Neural blind beamformer for cyclostationary signals," in Journal of Systems Engineering and Electronics, vol. 16, no. 3, pp. 498-501, Sept. 2005.
doi: 10.1109/WCACEM.2005.1469597
Abstract: A blind beamforming algorithm based on a neural network is presented according to the characteristic of cyclostationary signals. This method transforms the question of estimating beamformer weight vectors into the one of computing the SVD of the cross correlation matrix of array input signals and their frequency shift signals. A cross correlation neural network is introduced to compute the SVD of the cross correlation matrix so as to reduce the computational complexity and carry out the blind beamforming more efficiently. The improved cross-coupled Hebbian learning rule presented can make the weights of the neural network converge much fast. Therefore, it is more promising in the practical use. This method can restrain noise and interference. Simulation proves its correctness.
keywords: {Array signal processing;Arrays;Correlation;Interference;Neural networks;Vectors;blind beamforming;cyclostationarity signals;neural network I;simulation},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6071192&isnumber=6071185

H. You, D. Yunlong and W. Guohang, "New structure of Kalman filter for radar networking," in Journal of Systems Engineering and Electronics, vol. 16, no. 2, pp. 241-244, June 2005.
Abstract: Due to the different data rates of the sensors and communication delays in the radar netting, the research of the asynchronous multisensor data fusion problem is more practical than that of the synchronous one. Through discussing the sequential approach, which is the classical asynchronous multisensor data fusion algorithm, a new algorithm based on distributed computation structure is proposed. The new algorithm can meet the requirement of real-time computation of netting fusion system, and is more practical for engineering compared with the classical sequential approach. Simulation results show the validity of the presented algorithm.
keywords: {Kalman filters;Radar tracking;Sensor fusion;Target tracking;Time measurement;asynchronous;fusion;multi-sensor;radar networking;sequential},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6071143&isnumber=6071138

H. You and Z. Jingwei, "New track correlation algorithms in a multisensor data fusion system," in IEEE Transactions on Aerospace and Electronic Systems, vol. 42, no. 4, pp. 1359-1371, October 2006.
doi: 10.1109/TAES.2006.314577
Abstract: In order to resolve the problem of track-to-track association in a distributed multisensor situation, this paper presents independent and dependent sequential track correlation algorithms based on Singer's and Bar-Shalom's algorithms. Based on sequential track correlation algorithm, the restricted and attenuation memory track correlation algorithms and sequential classic assignment rules are proposed. In this paper, these algorithms are described in detail. Then, the track correlation mass and multivalency processing methods are discussed as well. Finally, simulations are designed to compare the correlation performance of these algorithms with that of Singer's and Bar-Shalom's algorithms. The simulation results show that the performance of these algorithms proposed here is much better than that of the classical methods under the environments of dense targets, interfering, noise, track cross, and so on. Under the above situations, their correct correlation ratio is improved about 69 percent over the classical methods
keywords: {correlation methods;distributed sensors;sensor fusion;Bar-Shalom algorithm;Singer algorithm;attenuation memory;distributed multisensor;multisensor data fusion system;multivalency processing;restricted memory;sequential track correlation;track-to-track association;Aerospace engineering;Attenuation;Covariance matrix;Gaussian noise;Multisensor systems;Noise measurement;Target tracking;Testing;Time measurement;Working environment noise},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=4108006&isnumber=4107974

Z. Li, L. Lingyun and H. You, "New multi-layer data correlation algorithm for multi-passive-sensor location system," in Journal of Systems Engineering and Electronics, vol. 18, no. 4, pp. 667-672, Dec. 2007.
doi: 10.1016/S1004-4132(08)60001-8
Abstract: Under the scenario of dense targets in clutter, a multi-layer optimal data correlation algorithm is proposed. This algorithm eliminates a large number of false location points from the assignment process by rough correlations before we calculate the correlation cost, so it avoids the operations for the target state estimate and the calculation of the correlation cost for the false correlation sets. In the meantime, with the elimination of these points in the rough correlation, the disturbance from the false correlations in the assignment process is decreased, so the data correlation accuracy is improved correspondingly. Complexity analyses of the new multi-layer optimal algorithm and the traditional optimal assignment algorithm are given. Simulation results show that the new algorithm is feasible and effective.
keywords: {Accuracy;Algorithm design and analysis;Complexity theory;Correlation;Heuristic algorithms;Simulation;Size measurement;correlation cost;data correlation;location system;multi layer correlation algorithm;multi passive-sensor},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6071667&isnumber=6071662

H. You, X. Wei and M. Qiang, "Composite filtering with feedback information," in Journal of Systems Engineering and Electronics, vol. 18, no. 1, pp. 54-56, March 2007.
doi: 10.1016/S1004-4132(07)60050-4
Abstract: The optimal fusion solution with feedback information for a hybrid multisensor data fusion system is presented. In this system, a part of sensors process their data locally to produce local tracks, and another part of sensors only provide detection reports These tracks and detection reports are communicated to a central site where track fusion and composite filtering are performed. The comparative results on the simulations suggest the feedback information from the center can greatly improve the tracking performance of the local node.
keywords: {Filtering;Noise;Radar tracking;Sensor fusion;Sensor systems;Target tracking;Data fusion;Filtering;Hybrid system;Multisensor tracking},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6071720&isnumber=6071706

H. Lifang, G. Xin and H. You, "Efficient combination rule of Dezert-Smarandache theory," in Journal of Systems Engineering and Electronics, vol. 19, no. 6, pp. 1139-1144, Dec. 2008.
doi: 10.1016/S1004-4132(08)60210-8
Abstract: The Dezert-Smarandache theory (DSmT) is a useful method for dealing with uncertainty problems. It is more efficient in combining conflicting evidence. Therefore, it has been successfully applied in data fusion and object recognition. However, there exist shortcomings in its combination rule. An efficient combination rule is presented, that is, the evidence's conflicting probability is distributed to every proposition based on remaining the focal elements of conflict. Experiments show that the new combination rule improves the reliability and rationality of the combination results. Although evidences conflict another one highly, good combination results are also obtained.
keywords: {Accuracy;Cognition;Helium;Object recognition;Sensors;Simulation;Uncertainty;DSmT;object recognition;the focal element of conflict},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6072448&isnumber=6072431

H. You, Z. Hongwei and T. Xiaoming, "Joint systematic error estimation algorithm for radar and automatic dependent surveillance broadcasting," in IET Radar, Sonar & Navigation, vol. 7, no. 4, pp. 361-370, April 2013.
doi: 10.1049/iet-rsn.2012.0199
Abstract: Systematic error of radar cannot be accurately determined solely with the use of an automatic dependent surveillance broadcasting (ADS-B) device. This is largely, because of the device's inability to obtain the exact transmitting time of ADS-B data packets. In order to study and establish an efficient and accurate error registration algorithm for radars based on the ADS-B system, a joint systematic error estimation model of the radar and ADS-B was built. The authors showed that when receiving time is known, the time difference between radar measuring time and ADS-B data transmitting time is consistently biased, a feature that can be used to calculate the systematic error of the ADS-B receiving system. Then, they established an error estimation model based on the joint systematic error of the radar and ADS-B. The generalised least squares estimation method was adopted to solve the model. Finally, data samples verified the accuracy and effectiveness of the error registration algorithm.
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6573718&isnumber=6573714

G. Jian, L. Ning-Bo, H. Yong and H. You, "Fractal Poisson Model for Target Detection Within Spiky Sea Clutter," in IEEE Geoscience and Remote Sensing Letters, vol. 10, no. 2, pp. 411-415, March 2013.
doi: 10.1109/LGRS.2012.2203578
Abstract: This letter introduces a kind of algebraic fractal model-Paretian Poisson process to the field of sea spike modeling and target detection. Sea spikes are strong rapidly varying echoes lasting for up to some seconds, which can be judged from the clutter background according to three parameters, i.e., the spike amplitude, the minimum spike width, and the minimum interval between spikes. Paretian Poisson process performs well in describing a power-law connection between positive-valued measurements and their occurrence frequencies. In this letter, Paretian Poisson process is used for modeling the relation between the spike durations and the spikes' occurrence frequencies. By the verification of X-band radar data, we find that Paretian Poisson process can well model sea spikes, and its parameters, the Paretian exponent and the residual sum of squares, have the potential for distinguishing targets from sea spikes. Consequently, a target detection method is proposed, and the detecting performance is analyzed. The results show that the proposed method performs well in target detection except the high requirement of the quantity of samples.
keywords: {algebra;oceanographic equipment;oceanographic techniques;radar clutter;radar detection;stochastic processes;Paretian exponent;X-band radar data verification;algebraic fractal model-Paretian Poisson process;clutter background;positive-valued measurements;power-law connection;sea spike modeling;spike amplitude;spike durations;spike occurrence frequencies;spiky sea clutter;target detection method;Clutter;Correlation;Detectors;Fractals;Object detection;Radar;Thyristors;Algebraic fractal;Paretian Poisson;sea clutter;sea spike;target detection},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6276236&isnumber=6336843

L. Yu, H. You and W. Haipeng, "Squared-root cubature information consensus filter for non-linear decentralised state estimation in sensor networks," in IET Radar, Sonar & Navigation, vol. 8, no. 8, pp. 931-938, October 2014.
doi: 10.1049/iet-rsn.2013.0283
Abstract: Distributed analysis of target kinematics captured by a large network of sensors has received significant attention lately. Tracking moving targets in nonlinear systems is one of the most fundamental tasks in this regard and information-type consensus filters (ICFs) have been applied to this problem. To improve the estimate performance, a squared-root cubature information filter which can avoid numerically sensitive matrix operations such as matrix square-rooting and inversion has been developed firstly. And then, based on this filter, a decentralised information filtering algorithm is proposed in an improved consensus framework. Specifically, consensus update at each time-cycle in the modified consensus scheme is computed in two steps, first towards the predicted value and then towards the final information estimate update, which can improve average estimation accuracy and speed the average consensus. Besides the basic merits of the traditional ICFs, the resulting algorithm is more scalable and robust. Simulation results clearly show the advantage of the proposed algorithm compared with existing ICFs in the considered application scenario.
keywords: {filtering theory;information filters;sensor fusion;state estimation;target tracking;decentralised information filtering algorithm;distributed analysis;information-type consensus filters;inversion;matrix square-rooting;moving target tracking;nonlinear decentralised state estimation;nonlinear systems;numerically sensitive matrix operations;sensor networks;squared-root cubature information consensus filter;target kinematics},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6911071&isnumber=6911062
X. Cong'an, J. Tao, D. Kai, Q. Lin and H. You, "An initialization clustering method for SMC-PHD based on likelihood function," IET International Radar Conference 2015, Hangzhou, 2015, pp. 1-4.
doi: 10.1049/cp.2015.1413
Abstract: The sequential Monte Carlo probability hypothesis density (SMC-PHD) filter has been demonstrated an elegant multi-target tracking algorithm which is suitable for highly nonlinear systems. However, as a typical technique of extracting multi-target state for SMC-PHD, standard K-means clustering is unreliable due to the initialization, which chooses the initial cluster centers at random. To solve the problem of the K-means clustering, an initialization method for SMC-PHD based on likelihood function is proposed in this paper. First the likelihood function based statistic is defined and the selection of threshold used to obtain the target-generated measurements is illustrated. Then a novel initialization method is discussed in detail. Finally simulations are presented. The results show that the proposed method has better performance than the standard K-means clustering.
keywords: {Monte Carlo methods;nonlinear systems;pattern clustering;probability;target tracking;tracking filters;K-means clustering;SMC-PHD filter;likelihood function based statistic;multitarget state extraction;multitarget tracking algorithm;nonlinear system;sequence initialization clustering method;sequential Monte Carlo probability hypothesis density filter;Initialization clustering;Likelihood function;Multi-target tracking (MTT);Sequential Monte Carlo probability hypothesis density (SMC-PHD)},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7455635&isnumber=7441332

M. Xubing, J. Tao, H. You and D. Biao, "A novel Bayesian adaptive detector against non-Gaussian clutter," IET International Radar Conference 2015, Hangzhou, 2015, pp. 1-4.
doi: 10.1049/cp.2015.1282
Abstract: We present a novel two-step radar signal detector against the non-Gaussian distributed clutter in this paper. The compound Gaussian distribution is employed to model the clutter, which describes the clutter vector as the product of a non-negative random variable (the so-called texture) with a complex Gaussian random vector (called the speckle). The posteriori probability density function of the texture parameter is given by the Bayesian approach using a non-informative priori. Then the expression of testing statistic is derived according to likelihood ratio test rules. The Monte Carlo simulation is taken to investigate the performance of the detector in several kinds of clutter environments and the results show its improvement compared to the conventional adaptive matched filter detector.
keywords: {Bayes methods;Gaussian distribution;Monte Carlo methods;adaptive signal detection;radar clutter;radar detection;Bayesian adaptive detector;Gaussian distribution;Monte Carlo simulation;complex Gaussian random vector;likelihood ratio test rule;non-Gaussian distributed clutter;nonnegative random variable product;posteriori probability density function;testing statistic;texture parameter;two-step radar signal detector;Bayesian approach;Compound Gaussian distribution;Radar signal detector;a non-informative priori;posteriori probability density function},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7455504&isnumber=7441332

T. Jian, G. Liao, Y. He and J. Shen, "A CFAR detector based on orthogonal wavelet transform," 2014 12th International Conference on Signal Processing (ICSP), Hangzhou, 2014, pp. 1963-1967.
doi: 10.1109/ICOSP.2014.7015336
Abstract: Radar target constant false alarm rate (CFAR) detection in wavelet domain is elementarily investigated in this paper. Theoretical analysis shows that independent and identically distributed Gaussian noise keeps the independence and variance invariable through the orthogonal wavelet transform. In the proposed detector, orthogonal wavelet transform is applied to radar echo signal and the wavelet coefficients are obtained. And then a squarer detector is utilized. After that, according to the characteristic of Gaussian noise in orthogonal wavelet domain, a cell average-CFAR detector model based on orthogonal wavelet transform is established. The probability equations of false alarm and detection are also deduced, and the influence of the wavelet coefficient length on detection performance is analyzed. Finally, the experiment results demonstrate that the proposed method can detect target under different false alarm rates effectively and adaptively.
keywords: {Gaussian distribution;Gaussian noise;probability;radar detection;wavelet transforms;Gaussian noise distribution;cell average-CFAR detector model;orthogonal wavelet transform;probability equation;radar echo signal;radar target constant false alarm rate detection;squarer detector;wavelet coefficient;Detectors;Gaussian noise;Radar;Wavelet coefficients;cell average;constant false alarm rate;orthogonal wavelet transform;radar target detection},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7015336&isnumber=7014954

L. Yu, H. You and W. Haipeng, "Squared-root cubature information consensus filter for non-linear decentralised state estimation in sensor networks," in IET Radar, Sonar & Navigation, vol. 8, no. 8, pp. 931-938, October 2014.
doi: 10.1049/iet-rsn.2013.0283
Abstract: Distributed analysis of target kinematics captured by a large network of sensors has received significant attention lately. Tracking moving targets in nonlinear systems is one of the most fundamental tasks in this regard and information-type consensus filters (ICFs) have been applied to this problem. To improve the estimate performance, a squared-root cubature information filter which can avoid numerically sensitive matrix operations such as matrix square-rooting and inversion has been developed firstly. And then, based on this filter, a decentralised information filtering algorithm is proposed in an improved consensus framework. Specifically, consensus update at each time-cycle in the modified consensus scheme is computed in two steps, first towards the predicted value and then towards the final information estimate update, which can improve average estimation accuracy and speed the average consensus. Besides the basic merits of the traditional ICFs, the resulting algorithm is more scalable and robust. Simulation results clearly show the advantage of the proposed algorithm compared with existing ICFs in the considered application scenario.
keywords: {filtering theory;information filters;sensor fusion;state estimation;target tracking;decentralised information filtering algorithm;distributed analysis;information-type consensus filters;inversion;matrix square-rooting;moving target tracking;nonlinear decentralised state estimation;nonlinear systems;numerically sensitive matrix operations;sensor networks;squared-root cubature information consensus filter;target kinematics},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6911071&isnumber=6911062

S. C. Lai, W. C. Li, S. H. You, D. W. Jhuang and S. T. Gao, "Low-Cost and Low-Complexity Electrocardiogram Signal Recorder Design Based on Arduino Platform," Intelligent Information Hiding and Multimedia Signal Processing (IIH-MSP), 2014 Tenth International Conference on, Kitakyushu, 2014, pp. 309-312.
doi: 10.1109/IIH-MSP.2014.83
Abstract: This paper presents an acquisition circuit design integrated with commercial ICs and platform is built for the development of long-term ECG monitor. An efficient DCT-IV-based ECG compression algorithm with a higher Quality Score (QS) and a better Compressing Ratio (CR) is further embedded to reduce a great number of recording data in storage and transmission. To fairly evaluate the performance of the proposed compressing algorithm, the ECG signals sourced from MIT-BIT arrhythmia database with a sampling rate of 360 Hz are employed to be the test patterns. The simulation results show that the averages of CR, Percent RMS Difference (PRD), and QS are, respectively, 5.267, 0.187, and 28.223 for all 48 lead-V1 patterns of MIT-BIH database. Compared with the Lee et al.'s algorithm, the QS value of the proposed method has a great improvement by 25%. Finally, we successfully combine the above works into a system and make a detailed comparison with state-of-the-art approach. The experiment results clearly show that the proposed system would be a better choice for realizing ECG signal acquisition in the future.
keywords: {data compression;discrete cosine transforms;electrocardiography;medical signal detection;Arduino platform;CR;DCT-IV-based ECG compression algorithm;ECG signals;MIT-BIT arrhythmia database;QS;compressing ratio;electrocardiogram signal recorder design;long-term ECG monitor;quality score;signal acquisition circuit design;Algorithm design and analysis;Biomedical monitoring;Compression algorithms;Electrocardiography;Monitoring;Wireless communication;Wireless sensor networks;Arduino;compression algorithm;electrocardiogram (ECG);the type-IV of discrete cosine transform (DCT-IV)},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6998329&isnumber=6998244

Song Jie, Long Teng and He You, "Adaptive cancellation of direct wave interference based on a new variable-step-size NLMS algorithm," Radar Conference 2013, IET International, Xi'an, 2013, pp. 1-4.
doi: 10.1049/cp.2013.0318
Abstract: On the basis of the analyses of the conventional LMS algorithm, normalized LMS algorithm, and variable-step-size LMS algorithm, a new variable-step-size normalized LMS (New VSSNLMS) algorithm is proposed, and the superiority of the algorithm is verified by the computer simulation. The proposed algorithm is applied to adaptive cancellation of direct wave interference in passive bistatic pulse radar. Experiments shows a fast convergence rate as well as a small output error are obtained by the New VSSNLMS algorithm.
keywords: {adaptive signal processing;passive radar;radar interference;adaptive cancellation;computer simulation;direct wave interference;passive bistatic pulse radar;variable-step-size NLMS algorithm;variable-step-size normalized LMS algorithm;Adaptive Cancellation;LMS;Passive;Radar},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6624482&isnumber=6624271

H. You, Z. Hongwei and T. Xiaoming, "Joint systematic error estimation algorithm for radar and automatic dependent surveillance broadcasting," in IET Radar, Sonar & Navigation, vol. 7, no. 4, pp. 361-370, April 2013.
doi: 10.1049/iet-rsn.2012.0199
Abstract: Systematic error of radar cannot be accurately determined solely with the use of an automatic dependent surveillance broadcasting (ADS-B) device. This is largely, because of the device's inability to obtain the exact transmitting time of ADS-B data packets. In order to study and establish an efficient and accurate error registration algorithm for radars based on the ADS-B system, a joint systematic error estimation model of the radar and ADS-B was built. The authors showed that when receiving time is known, the time difference between radar measuring time and ADS-B data transmitting time is consistently biased, a feature that can be used to calculate the systematic error of the ADS-B receiving system. Then, they established an error estimation model based on the joint systematic error of the radar and ADS-B. The generalised least squares estimation method was adopted to solve the model. Finally, data samples verified the accuracy and effectiveness of the error registration algorithm.
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6573718&isnumber=6573714

Song Jie, Long Teng and He You, "Design of navigation radar signal acquisition and analysis system," Radar Conference 2013, IET International, Xi'an, 2013, pp. 1-4.
doi: 10.1049/cp.2013.0113
Abstract: In order to testify the algorithms for the detection of wake targets in sea clutter background, a navigation radar signal acquisition and analysis system is developed. The system uses USB2.0 as the interface of microcomputer and works with FPGA as its kernel chip. Experimental results show that it can satisfy the data acquisition and analysis tasks of the navigation radar. The system can record and store the original information for later processing, to analysize the various characteristics of targets and clutter. It provides the basis for radar signal processing and target detection algorithm.
keywords: {field programmable gate arrays;radar clutter;radar computing;radar signal processing;signal detection;target tracking;FPGA;USB2.0;data acquisition;kernel chip;microcomputer;navigation radar signal acquisition;navigation radar signal analysis;radar signal processing;sea clutter background;wake target detection;Data Acquisition and Analysis;Navigation Radar;Sea Clutter},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6624277&isnumber=6624271

S. Jie, Y. Hang, G. Chengbin, L. Teng and H. You, "Design and implementation of signal generator and real-time analysis system," 2013 25th Chinese Control and Decision Conference (CCDC), Guiyang, 2013, pp. 4517-4520.
doi: 10.1109/CCDC.2013.6561749
Abstract: A FPGA-based two-channel low frequency signal generator and analysis system has been designed to analyze the occurrence and analysis of low frequency signal. It uses FPGA for low frequency signal producing control chip module and analysis module. Control signal is sent to the FPGA by keys, FPGA generates frequency range step adjustable low frequency signal. Through the adder, fast Fourier transform is used to extract frequency domain signal by analysis module FPGA, the oscilloscope measures frequency amplitude and other information, to achieve low frequency signal frequency domain analysis capabilities. The system whose encapsulation is compact has friendly interface and it is very easy to operate and demonstrate.
keywords: {adders;fast Fourier transforms;field programmable gate arrays;frequency measurement;frequency-domain analysis;oscilloscopes;real-time systems;signal generators;FPGA;adder;fast Fourier transform;frequency amplitude measurement;frequency domain signal extraction;low frequency signal producing control chip module;oscilloscope;real-time analysis system;signal analysis module;signal frequency domain analysis;signal generator;step adjustable low frequency signal;Adders;Field programmable gate arrays;Frequency control;Frequency-domain analysis;Signal generators;Spectral analysis;FPGA;fast Fourier transform;frequency domain analysis;signal generation},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6561749&isnumber=6560882

G. Jian, L. Ning-Bo, H. Yong and H. You, "Fractal Poisson Model for Target Detection Within Spiky Sea Clutter," in IEEE Geoscience and Remote Sensing Letters, vol. 10, no. 2, pp. 411-415, March 2013.
doi: 10.1109/LGRS.2012.2203578
Abstract: This letter introduces a kind of algebraic fractal model-Paretian Poisson process to the field of sea spike modeling and target detection. Sea spikes are strong rapidly varying echoes lasting for up to some seconds, which can be judged from the clutter background according to three parameters, i.e., the spike amplitude, the minimum spike width, and the minimum interval between spikes. Paretian Poisson process performs well in describing a power-law connection between positive-valued measurements and their occurrence frequencies. In this letter, Paretian Poisson process is used for modeling the relation between the spike durations and the spikes' occurrence frequencies. By the verification of X-band radar data, we find that Paretian Poisson process can well model sea spikes, and its parameters, the Paretian exponent and the residual sum of squares, have the potential for distinguishing targets from sea spikes. Consequently, a target detection method is proposed, and the detecting performance is analyzed. The results show that the proposed method performs well in target detection except the high requirement of the quantity of samples.
keywords: {algebra;oceanographic equipment;oceanographic techniques;radar clutter;radar detection;stochastic processes;Paretian exponent;X-band radar data verification;algebraic fractal model-Paretian Poisson process;clutter background;positive-valued measurements;power-law connection;sea spike modeling;spike amplitude;spike durations;spike occurrence frequencies;spiky sea clutter;target detection method;Clutter;Correlation;Detectors;Fractals;Object detection;Radar;Thyristors;Algebraic fractal;Paretian Poisson;sea clutter;sea spike;target detection},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6276236&isnumber=6336843

X. Gu, T. Jian, Y. Wang and Y. He, "An inhomogeneous clutter-clustered estimation method of covariance matrix," Signal Processing (ICSP), 2012 IEEE 11th International Conference on, Beijing, 2012, pp. 1808-1812.
doi: 10.1109/ICoSP.2012.6491931
Abstract: This paper addresses the problem of covariance matric estimation for radar adaptive constant false alarm rate (CFAR) detection in clutter-dominated disturbance modeled as compound-Gaussian process. For estimation purposes we resort to range cells, free of signal components, can be clustered into groups of data with one and the same value of texture. Extending the homogeneous clutter-clustered estimator to a more generalized situation and an inhomogeneous clutter-clustered estimator (ICCE) is obtained. Furthermore, to improve the estimation accuracy a recursive ICCE (RICCE) is proposed. The ICCE and the RICCE both have the CFAR property with respect to the statistics of the texture and the clutter covariance matrix. Compared with the existing estimators, the simulation shows that the RICCE has the higher estimated accuracy.
keywords: {Gaussian processes;covariance matrices;estimation theory;pattern clustering;radar clutter;radar resolution;radar signal processing;CFAR detection;CFAR property;RICCE;clutter covariance matrix estimation;clutter-dominated disturbance modeled;compound-Gaussian process;inhomogeneous clutter-clustered estimation method;inhomogeneous clutter-clustered estimator;radar adaptive constant false alarm rate detection;recursive ICCE;signal components;texture statistics;texture value;clutter-clustered;constant false alarm rate;covariance matrix estimation;non-Gaussian clutter;normalized matched filter},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6491931&isnumber=6491878

Tang Ning and He You-shi, "A study of the current application status in Chinese E-Government outsourcing," 2012 International Conference on Information Management, Innovation Management and Industrial Engineering, Sanya, 2012, pp. 9-11.
doi: 10.1109/ICIII.2012.6339651
Abstract: Outsourcing is one of the most popular forms used in the current E-Government outsourcing construction. With continuing development of information technology and the emerging idea of building the service-oriented government, the operation of E-Government outsourcing in China has come into a more mature period now. This paper discusses the current application status of E-Gov outsourcing in China from introducing some specific outsourcing cases in different places of China. This paper also discusses the developing period of E-Gov outsourcing in China and comes to the conclusion that China has already come into the operating and maintaining outsourcing period. Then it discusses the model of E-Gov outsourcing that used popularly, as well as existing risk factors, problems and their solutions.
keywords: {government data processing;outsourcing;service-oriented architecture;Chinese e-government outsourcing construction;application status;information technology;outsourcing period maintenance;outsourcing period operation;risk factors;service-oriented government;Buildings;Companies;Contracts;Electronic government;Maintenance engineering;Outsourcing;E-Government;Outsourcing;Outsourcing model;Risk management},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6339651&isnumber=6339626

Ding Hao, Huang Yong, Song Jie, Guan Jian and He You, "Sea state parameters extraction from radar images: System design and implementation," Proceedings of 2011 IEEE CIE International Conference on Radar, Chengdu, 2011, pp. 821-824.
doi: 10.1109/CIE-Radar.2011.6159668
Abstract: The main concentration of this paper is the system design and implementation of sea state parameters retrieval technique from nautical radar. The system consists of three main components: a general sea clutter data acquisition subsystem, a standard computer and a software package. The data acquisition subsystem is designed to acquire sea clutter data and then form consecutive image sequence for further analysis. The standard computer stores the acquired data and offers a hardware platform for the entire system. The software package with program language of Visual C++ fulfills the realization of the retrieval algorithms. Experimental results show the effectiveness and feasibility of the research. This work has significant values not only for ocean engineering but also for the performance of radar system in the detection of dim targets in strong sea clutter.
keywords: {C++ language;Visual BASIC;data acquisition;image sequences;marine radar;object detection;ocean waves;radar clutter;radar imaging;Visual C++;consecutive image sequence;data acquisition subsystem;dim target detection;general sea clutter;nautical radar;ocean engineering;program language;radar images;sea state parameters extraction;sea state parameters retrieval;software package;standard computer;Clutter;Data acquisition;Radar antennas;Radar imaging;Sea surface;Surface waves;Sea state parameters;dim targets detection;retrieval algorithms;sea clutter data acquisition system},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6159668&isnumber=6159460

C. Zhang, Tang Xiaoming, Y. He and J. Ding, "Analysis of amplitude modulation effect on pulsed passive coherent location system," Proceedings of 2011 IEEE CIE International Conference on Radar, Chengdu, 2011, pp. 1029-1032.
doi: 10.1109/CIE-Radar.2011.6159727
Abstract: The purpose of this paper is to analysis the amplitude modulation effect caused by the rotating transmit antenna pattern, which results in pulses loss within the direct-path pulse train. The loss mechanisms of signal to noise ratio (SNR) were discussed for these modulation phenomena. The analytical expression of the peak output of cross-ambiguity function was derived, which correspond to the cases of pulses loss occurrence. Simulation results show that the maximum SNR loss is less than 4 dB in the worst case, and the SNR loss curves for various Doppler frequencies and different number of pulse loss are conformed to the theoretical analysis. The worst Doppler frequency estimation bias is about 0.75 times the frequency resolution cell when there is no ambiguity in Doppler estimation.
keywords: {Doppler effect;amplitude modulation;antenna radiation patterns;frequency estimation;transmitting antennas;amplitude modulation;cross ambiguity function;direct path pulse train;frequency resolution cell;pulsed passive coherent location system;pulses loss occurrence;rotating transmit antenna pattern;signal to noise ratio;worst Doppler frequency estimation bias;Doppler shift;Frequency estimation;Passive radar;Signal to noise ratio;Transmitting antennas;Antenna Pattern;Cross-Ambiguity Function (CAF);Direct-Path Pulses Loss;Passive Coherent Location (PCL)},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6159727&isnumber=6159713

Wang Hai-peng, Xiong Wei and He You, "Centralized multisensor general association algorithm based on data compress technique," Proceedings of 2011 IEEE CIE International Conference on Radar, Chengdu, 2011, pp. 1830-1833.
doi: 10.1109/CIE-Radar.2011.6159928
Abstract: Aim to solve the problem that the memory of the centralized multi-sensor system is easy to be saturated, this paper has proposed a new algorithm named centralized multi-sensor general association algorithm based on data compress technique against a background, which has a relative demand of real-time and tracking precision. In this algorithm, the measurement sets associated with the same target from each sensor are obtained and compressed into equivalents. A lot of association hypotheses are built with the equivalents, the remainder measurements and the track of each target. The score of every hypothesis could be obtained with the formula of the score function in multi-sensor general association algorithm, and the state estimation of the fusion center is gained finally. The simulation results show that this algorithm could track the targets effectively with the high density clutter and the general performance of this algorithm is better than that of sequential centralized multi-sensor joint probabilistic data association algorithm and parallel centralized multi-sensor general association algorithm.
keywords: {data compression;sensor fusion;association hypotheses;centralized multisensor general association algorithm;centralized multisensor joint probabilistic data association algorithm;data compress technique;fusion center;high density clutter;relative demand;remainder measurements;score function;state estimation;target tracking;tracking precision;Accuracy;Clutter;Data compression;Measurement uncertainty;Radar tracking;Real time systems;Target tracking;centralized;data compress;general association;memory saturation;score function},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6159928&isnumber=6159713

Zhu HongWei, Song Qiang, G. Wang and He You, "System errors estimation of DOA and TDOA jointed locating system using sequential least squares," Proceedings of 2011 IEEE CIE International Conference on Radar, Chengdu, 2011, pp. 1025-1028.
doi: 10.1109/CIE-Radar.2011.6159726
Abstract: To estimate system errors of direction of arrival (DOA) and time difference of arrival (TDOA) with two stations locating system, a system error estimation model is build through analyzing the locating principle. In succession sequential least squares estimation (SLSE) is studied. And then he estimation process is given. At last convergence and accuracy of SLSE are researched through Monte Carlo simulation. And target tracks which are before and after the bias registration are compared. Theoretical analyses and simulation shows that the SLSE can exactly and effectively estimate system errors of DOA and TDOA locating system.
keywords: {Monte Carlo methods;direction-of-arrival estimation;least squares approximations;radar tracking;target tracking;time-of-arrival estimation;DOA-and-TDOA jointed locating system;Monte Carlo simulation;SLSE accuracy;SLSE convergence;TDOA locating system;direction of arrival;estimation process;locating principle;sequential least squares estimation;stations locating system;system errors estimation model;target tracking;time difference of arrival;Direction of arrival estimation;Error analysis;Estimation;Measurement uncertainty;Noise;Noise measurement;Target tracking;direction of arrival and time difference of arrival jointed locating system;errors estimation model;sequential least squares estimation;system errors estimation},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6159726&isnumber=6159713

H. Li, Y. He, H. q. Zhou and J. Peng, "A new method for direct signal recover in non-cooperative bistatic radar," Electric Information and Control Engineering (ICEICE), 2011 International Conference on, Wuhan, 2011, pp. 1055-1058.
doi: 10.1109/ICEICE.2011.5777671
Abstract: The direct signal which includes noise and multipath clutter greatly declines the performance of the non-cooperation bistatic radar system. To mitigate this problem, a new method based on three-sensor array for direct signal recover in non cooperation bistatic radar is proposed. The expression of recovering direct signal from white noise and multipath clutter is analyzed in detail. Statistical performances of the method are provided by computer simulation. The theoretical analysis and simulation result shows that the new method can recover the direct signal effectively from noise and multipath clutter.
keywords: {radar clutter;radar signal processing;white noise;direct signal recovery;multipath clutter;non-cooperative bistatic radar;three-sensor array;white noise;Arrays;Bistatic radar;Chirp;Chirp modulation;Clutter;Frequency modulation;Noise;direct signal;non-cooperative bistatic radar;recover;signal matched phase},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5777671&isnumber=5776798

H. Li, Y. He, H. q. Zhou and X. m. Tang, "A signal-to-noise ratio enhancement method for non-cooperative bistatic radar system," Proceedings of 2011 IEEE CIE International Conference on Radar, Chengdu, 2011, pp. 919-923.
doi: 10.1109/CIE-Radar.2011.6159691
Abstract: In non-cooperation bistatic radar system, the target detection performance of the system is degraded by the background clutter and random noise. In order to solve this problem, a new method based on signal phase matching for signal-to-noise ratio (SNR) enhancement is proposed. It fully uses the phase differences of target signals and interference signals. The target signals are successfully separated from the background clutter and random noise according to the signal phase matching. The simulation results show that this method can effectively suppress the background clutter and random noise and remarkably enhance the SNR of the non-cooperation bistatic radar system, which has important and practical significance in improving the target detection performance of the non-cooperation bistatic radar system.
keywords: {interference (signal);radar clutter;radar detection;radar target recognition;SNR enhancement;background clutter;interference signals;noncooperative bistatic radar system;signal phase matching;signal-to-noise ratio enhancement;signal-to-noise ratio enhancement method;target detection performance;Arrays;Bistatic radar;Clutter;Signal to noise ratio;background clutter;non-cooperation bistatic radar;random noise;signal-to-noise ratio},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6159691&isnumber=6159460

J. Xiu, Y. He and J. Xiu, "Study on maneuvering target adaptive tracking algorithm of 3D passive location system," Proceedings of 2011 IEEE CIE International Conference on Radar, Chengdu, 2011, pp. 1012-1015.
doi: 10.1109/CIE-Radar.2011.6159723
Abstract: In this paper we develop a simple yet more effective filtering algorithm for maneuvering target tracking of 3D Passive Location System by combination of pseudo linear filter with modified input estimation approach. In this method, the acceleration is treated as an additive input term in the corresponding state equation, and the augmented pseudo linear filter is used to solve the passive tracking problem of air maneuvering target. The original state and acceleration vectors are estimated simultaneously with the augmented pseudo linear filter. The proposed tracking algorithm operates in both the non-manoeuvring and the manoeuvring modes, and the manoeuvre detection procedure is eliminated. Simulation results show that using the method proposed in this paper passive sensor can track the maneuvering air target.
keywords: {filtering theory;object detection;target tracking;3D passive location system;acceleration vectors are;air maneuvering target;filtering algorithm;maneuvering target adaptive tracking algorithm;manoeuvre detection;modified input estimation approach;passive sensor;passive tracking problem;pseudo linear filter;Equations;Mathematical model;Maximum likelihood detection;Nonlinear filters;Radar tracking;Target tracking;Vectors;air manoeuvring target;augmented pseudo linear filter;modified input estimation;passive tracking},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6159723&isnumber=6159713

Cui Yaqi, Xiong Wei, He You and Li Runze, "Mobile sensor registration in ECEF coordinates using the MLR algorithm," Proceedings of 2011 IEEE CIE International Conference on Radar, Chengdu, 2011, pp. 1784-1787.
doi: 10.1109/CIE-Radar.2011.6159917
Abstract: A new algorithm is presented to align multiple 3-D mobile sensors in the Earth-Centred-Earth-Fixed coordinate system, which is called MLMR algorithm for short. The MLMR algorithm can effectively estimate sensor biases, sensor frame orientation and target state. For illustrative purposes, the MLMR algorithm is applied to simulated track data from two 3-D sensors.
keywords: {mobile radio;wireless sensor networks;ECEF coordinates;MLMR algorithm;earth-centred-earth-fixed coordinate system;mobile sensor registration;multiple 3-D mobile sensors;sensor network;Algorithm design and analysis;Coordinate measuring machines;Maximum likelihood estimation;Mobile communication;Signal processing algorithms;Trajectory;MLR algorithm;Registration;Sensor network},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6159917&isnumber=6159713

G. Xianjun, S. Jie and H. You, "Time delay and doppler shift estimation accuracy analyses of moving targets in non-cooperative bistatic pulse radar," IEEE 10th INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING PROCEEDINGS, Beijing, 2010, pp. 2291-2294.
doi: 10.1109/ICOSP.2010.5656265
Abstract: According to the characteristics of non-cooperative bistatic pulse radar systems and the issue that the doppler mismatched loss of the cross-correlation detection of moving targets is serious, two fast methods for joint time delay and doppler shift estimation of moving targets, based on segment correlation-FFT processing and modified partial segment correlation-FFT processing, are proposed, after analyzing the common methods for cross-ambiguity function processing such as direct calculation, FFT, Zoom-FFT method. The processing performance of direct calculation and partial segment correlation-FFT processing of LFM pulse-series is analyzed in theory and by simulation. And the simulation shows that the weak moving target can be detected effectively and the time delay and doppler shift can be fast estimated by the methods presented in this paper.
keywords: {Doppler shift;correlation methods;fast Fourier transforms;object detection;radar detection;Doppler shift estimation accuracy analysis;LFM pulse-series;cross-ambiguity function processing;cross-correlation detection;doppler mismatched loss;moving target detection;noncooperative bistatic pulse radar;partial segment correlation-FFT processing;time delay;Accuracy;Correlation;Delay effects;Doppler shift;Equations;Estimation;Mathematical model;bistatic radar;doppler shift;moving targets;non-cooperative;time delay},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5656265&isnumber=5654687

S. Yan-lin, H. You-bin, X. Xiao-hong, C. Yong-xiang and P. Gang, "The 3D modeling and visualization of geologic body based on GIS," Audio Language and Image Processing (ICALIP), 2010 International Conference on, Shanghai, 2010, pp. 533-537.
doi: 10.1109/ICALIP.2010.5684510
Abstract: Based on Geographic Information System(GIS) technology, the research of 3D geological modeling(3DGM) is carried out. The 3DGM method focused on complex geologic body is put forward, and modeling process is set up. First of all, according to the different strata, index layer of fault-block polygon is built. Then under the restraining of seismic interpretation surface and fault-block boundary, digital elevation model (DEM) tiles are built aiming at fault-block polygons in index layer. Based on index layer, DEM tiles are assembled into DEM of stratum aimed at index layer. Finally 3D structural model is built through overlaying DEM, and 3D geological model is generated based on 3D structural model. Taking Shu II district in the Liaohe Oilfield for example, 3D geological model of Dalinghe reservoir is successfully built based on this method. Visualization of model is realized through 3D GIS technology.
keywords: {data visualisation;digital elevation models;geographic information systems;reservoirs;solid modelling;3D modeling;3D visualization;Dalinghe reservoir;GIS;digital elevation model;fault-block polygons;geographic information system;geologic body;index layer;Geographic Information Systems;Geology;Indexes;Load modeling;Solid modeling;Surface treatment;Three dimensional displays},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5684510&isnumber=5683066

G. Xianjun, H. You and S. Jie, "Cross-correlation detection and time difference estimation in non-cooperative bistatic radar systems," IEEE 10th INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING PROCEEDINGS, Beijing, 2010, pp. 2261-2265.
doi: 10.1109/ICOSP.2010.5655147
Abstract: In this paper, the basic geometrical relationship and signal energy relationship of non-cooperative bistatic radar are introduced, and the method using the cross-correlation to obtain the time difference of direct signals and target scattering echoes in noisy environment is discussed. Some experiments have been done to simulate the process of cross-correlation detection and time difference estimation. What's more, on the basis of them, some parameters affecting the performance of the algorithm, such as the signal-noise ratio, pulse width and pulse number of cross-correlation, are analyzed by Monte Carlo simulation.
keywords: {Monte Carlo methods;correlation methods;radar signal processing;Monte Carlo simulation;cross-correlation detection;geometrical relationship;noncooperative bistatic radar system;pulse number;pulse width;signal energy relationship;signal-noise ratio;time difference estimation;Bistatic radar;Estimation;Frequency domain analysis;Receivers;Signal to noise ratio;bistatic radar;cross-correlation;non-cooperative;time difference},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5655147&isnumber=5654687

Z. Zhu and H. Y. Shi, "To Design and Validate the Comprehensive Evaluation Index System of City's Attraction of Offshore Software Outsourcing," E-Business and E-Government (ICEE), 2010 International Conference on, Guangzhou, 2010, pp. 2183-2187.
doi: 10.1109/ICEE.2010.552
Abstract: Offshore software outsourcing is a hot topic in the service outsourcing field. Based on the study of the existing references, this paper takes city's attraction of offshore software outsourcing as its research object and analyzes the meaning of offshore software outsourcing firstly. For setting up a comprehensive evaluation system, 30 quantitative and qualitative indexes are selected from three aspects of an undertake city, including industrial competitiveness, human resources competitiveness and basic environment competitiveness. This paper validates the comprehensive evaluation index system of city's attraction of offshore software outsourcing by RS evaluation method.
keywords: {human resource management;outsourcing;software development management;RS evaluation method;city attraction;comprehensive evaluation index system;human resources competitiveness;industrial competitiveness;offshore software outsourcing;undertake city;Cities and towns;Correlation;Humans;Indexes;Industries;Outsourcing;Software;city attraction;comprehensive evaluation index system;offshore software outsourcing;validity},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5592515&isnumber=5590383

W. Haipeng, H. You and X. Wei, "A Parallel Centralized Multi-sensor General Association Algorithm," Information Engineering (ICIE), 2010 WASE International Conference on, Beidaihe, Hebei, 2010, pp. 118-121.
doi: 10.1109/ICIE.2010.319
Abstract: This paper has researched on the problem of centralized multi-sensor multi-target tracking against a background, which has a high demand of real-time and a relative demand of tracking precision, and analyzed the advantages and disadvantages of the existent classical algorithms theoretically in this environment. Based on the research and the analysis, general association algorithm has been extended into multi-senor system through the parallel structure and a new algorithm named parallel centralized multi-sensor general association algorithm has been proposed. In this algorithm, a lot of hypotheses are built with the measurements of each sensor and the track of each target, the score of every hypothesis could be obtained with the formula of the score function in multi-sensor general association algorithm, and the state estimation of the fusion center is gained finally. The simulation results show that this algorithm could track the targets effectively with the high density clutter and the general performance of this algorithm is better than that of sequential centralized multi-sensor joint probabilistic data association algorithm and parallel centralized multi-sensor probabilistic nearest neighbor standard function.
keywords: {probability;sensor fusion;state estimation;target tracking;general association algorithm;joint probabilistic data association algorithm;multitarget tracking;parallel centralized multisensor;probabilistic nearest neighbor standard function;state estimation;Accuracy;Algorithm design and analysis;Clutter;Radar tracking;Real time systems;Signal processing algorithms;Target tracking;centralized;general association;parallel structure;real-time;the score function},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5572701&isnumber=5571632

J. Tao, S. Feng, H. You, G. Xuefeng and S. Jian, "Target detection of high-resolution radar in non-Gaussian clutter," IEEE 10th INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING PROCEEDINGS, Beijing, 2010, pp. 2047-2050.
doi: 10.1109/ICOSP.2010.5655836
Abstract: The high-resolution radar echo is modeled as a range-spread target. Based on the generalized likelihood ratio test design procedure, the range-spread target detection in spherically invariant random vector clutter is addressed. And a binary integrator with constant false alarm rate property is proposed to detect the whole range-spread target, after single target scatterer detection in each range cell. Finally, the performance assessment shows that, the detection performance is improved as the number of sensors used or the clutter spike increases, while it is robust to the clutter correlation.
keywords: {radar clutter;radar resolution;radar tracking;target tracking;binary integrator;clutter correlation;constant false alarm rate property;generalized likelihood ratio test design procedure;high-resolution radar echo;invariant random vector clutter;nonGaussian clutter;performance assessment;range-spread target detection;sensors;target scatterer detection;Clutter;Correlation;Detectors;Object detection;Radar detection;Thyristors;Monte Carlo simulation;generalized likelihood ratio test;high-resolution radar target detection;spherically invariant random vector},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5655836&isnumber=5654687

Z. Cai-sheng, T. Xiao-ming, H. You and D. Jia-hui, "Analysis of phase noise effect on noncooperative wideband bistatic receiver," Synthetic Aperture Radar, 2009. APSAR 2009. 2nd Asian-Pacific Conference on, Xian, Shanxi, 2009, pp. 257-260.
doi: 10.1109/APSAR.2009.5374094
Abstract: Noncooperative narrow-band coherent processing techniques have been developed, however, this capability for wideband signals processing require to investigate further. Of all the obstacles preventing coherent reception techniques from making transition into the optical domain, phase noise caused by system imperfections is one of them. This kind of phase error will defocus discrete scattering centres in the range-Doppler image, which will preclude target identification and analysis. The amount of phase noise in signal is directly related to its so-called bandwidth, the 3 dB line width of its power spectrum. Numerous investigators have studied the effects of laser phase noise. We will examine the effects it has on the performance of this receiver. Both theory and application of this original work is extended in this paper. The research defined a system configuration and assessed its potential performance via modelling. It was developed to support pulse compression of wideband waveforms for applications. The associated implementation issues introduced by electro-optical component characteristics were discussed. Coherent detection was used to implement difference mixing for subsequent digital processing.
keywords: {radar receivers;radar signal processing;synthetic aperture radar;ISAR;coherent detection;coherent reception techniques;digital processing;electro-optical component characteristics;narrow-band coherent processing techniques;noncooperative wideband bistatic receiver;optical domain;phase error;phase noise effect;power spectrum;range-Doppler image;Image analysis;Narrowband;Optical mixing;Optical noise;Optical pulse compression;Optical receivers;Optical scattering;Optical signal processing;Phase noise;Wideband;Coherent Integration;ISAR;Noncooperative Bistatic Receiver;Phase Noise},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5374094&isnumber=5374088

Y. s. He and Y. Qin, "Comprehensive Evaluation of City's Undertake Capability of Offshore Software Outsourcing in Jiangsu Province," 2009 First International Conference on Information Science and Engineering, Nanjing, 2009, pp. 2887-2892.
doi: 10.1109/ICISE.2009.412
Abstract: Offshore software outsourcing is a hot topic in the services outsourcing field. Based on the study of existing literature, and take city's undertake capability of offshore software outsourcing as its research object, this paper sets up a comprehensive evaluation system, 30 quantitative and qualitative indexes were selected from three aspects of a undertake city, including industrial competitiveness, competitiveness of human resources and basic environment. This paper evaluates the undertake capability of offshore software outsourcing of Nanking, Wuxi, Suzhou and Changzhou by weighted principal component TOPSIS value function model. And on the basis of evaluation results, some important suggestions and strategies are presented on upgrading cities undertake capability of offshore software outsourcing.
keywords: {DP industry;outsourcing;human resources competitiveness;industrial competitiveness;offshore software outsourcing;principal component TOPSIS value function model;qualitative indexes;quantitative indexes;services outsourcing field;Cities and towns;Communication industry;Computer industry;Costs;Humans;Information analysis;Law;Legal factors;Local government;Outsourcing},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5455435&isnumber=5454428

R. h. Zhang, Z. p. Jia, H. y. Cheng, X. Li and D. x. Han, "The Improved Scheme of Prolong-Lifetime in Wireless Sensor Networks," Embedded Software and Systems, 2009. ICESS '09. International Conference on, Zhejiang, 2009, pp. 372-378.
doi: 10.1109/ICESS.2009.32
Abstract: Due to the limited transmission range, data sensed by each sensor has to be forwarded in a multi-hop fashion before being delivered to the sink. The sensors closer to the sink have to forward comparatively more message than sensors at the periphery of the network, the nodes will deplete their batteries earlier. Besides the loss of the sensing capabilities of the nodes close to the sink, a more serious consequence of the death of the first tier of sensor nodes is the loss of connectivity between the nodes at the periphery of the network and the sink. It makes the wireless networks expire. To alleviate this undesired effect, we adopt two improved schemes. The first one is to redistribute the total energy budget with data traffic load; the second one is to balance the uneven traffic by power control method. They maximize the useful lifetime of the network. We show by theoretical analysis, as well as simulation, that they substantially improve the network lifetime.
keywords: {telecommunication network reliability;telecommunication traffic;wireless sensor networks;data traffic load;multihop wireless sensor network;network prolong-lifetime;power control method;total energy budget redistribution;Batteries;Communication system traffic control;Computer science;Embedded software;Energy consumption;Power control;Relays;Telecommunication traffic;Traffic control;Wireless sensor networks;lifetime;multi-hop;uneven traffic;wireless sensor networks},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5066671&isnumber=5066609

Song Jie, He You, Guan Jian and Tang Xiao-ming, "Direct wave reconstruction of non-cooperative bistatic pulse radar using modified CMA+MMA algorithm," Radar Conference, 2009 IET International, Guilin, 2009, pp. 1-5.
doi: 10.1049/cp.2009.0206
Abstract: The direct-path reference signal is affected by noise and multi-path interference signals. In order to restore the direct-path reference signal of non-cooperative bistatic pulse radar, the techniques of blind equalization are researched. Because the modulus of the direct-path signal is constant when the direct wave pulse is sustained, and is zero when the direct wave pulse is broken, the CMA and MMA algorithm in blind equalization algorithms are chosen as the proper algorithm. On the basis of the two algorithms, a modified CMA+MMA algorithm is proposed, and the validity of the algorithm is proved by using the computer simulation.
keywords: {blind equalisers;interference (signal);radar signal processing;signal reconstruction;blind equalization;constant modulus algorithm;direct wave reconstruction;direct-path reference signal;modified CMA+MMA algorithm;multimodulus algorithm;multipath interference signal;noncooperative bistatic pulse radar;Bistatic Radar;Blind Equalization;Direct Wave;Non-cooperative},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5367558&isnumber=5367270

Song Jie, He You, Guan Jian and Tang Xiao-ming, "Direct wave estimation of non-cooperative bistatic pulse radar using LMS adaptive filter," 2009 Chinese Control and Decision Conference, Guilin, 2009, pp. 2879-2882.
doi: 10.1109/CCDC.2009.5192690
Abstract: In this paper, an adaptive inverse filter is applied to estimate the non-cooperative bistatic pulse radar transmitted waveform from a clutter-corrupted direct-path signal, given some a-priori knowledge of the transmitted waveform. Some experiments have been done to simulate the process of direct wave reconstruction using LMS adaptive filter. The simulation results show that the adaptive filter does a fairly good job of mitigating the corruption of the direct-path signal.
keywords: {adaptive filters;estimation theory;least mean squares methods;radar clutter;radar signal processing;waveform analysis;LMS adaptive filter;adaptive inverse filter;clutter-corrupted direct-path signal;direct wave estimation;direct wave reconstruction;noncooperative bistatic pulse radar transmitted waveform;Adaptive filters;Bistatic radar;Electronic mail;Helium;Least squares approximation;Matched filters;Nonlinear filters;Propagation losses;Radar clutter;Space vector pulse width modulation;Adaptive Filter;Bistatic Radar;Direct Wave;Non-cooperative;Reconstruction},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5192690&isnumber=5191464

Li Jun, He You and Song Jie, "The algorithms and performance analysis of cross ambiguity function," Radar Conference, 2009 IET International, Guilin, 2009, pp. 1-4.
doi: 10.1049/cp.2009.0333
Abstract: In the article, three algorithms for cross ambiguity function are analyzed, also the flow charts of them are presented. Through computations and error comparison of these methods, the applicable scope of each method are obtained, which is proved by the simulation results of pseudo-voice signal. In practical application, the right method should be chosen to meet the needs.
keywords: {filtering theory;flowcharting;radar signal processing;cross ambiguity function;error comparison;flow charts;performance analysis;practical application;pseudo-voice signal;algorithm;ambiguity function;computations},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5367482&isnumber=5367270

J. Xiu, Y. Li, Y. He and G. Wang, "Association algorithm with bearing-only measurements in 3-Dimensional space," Radar Conference, 2009 IET International, Guilin, 2009, pp. 1-4.
doi: 10.1049/cp.2009.0394
Abstract: In this paper, a new method is studied to associate the bearing measurements of different passive sensors. This method uses multi-dimension assignment algorithm for reference, and the nearest-neighbor method is combined with the holistic correlation method to reduce the dimension of bearing measurements association. Then, the chi-square test is used to associate the bearing measurements. Compared with the classical methods, this method can eliminate false intersection points more quickly and correctly. Simulation results show that using the method proposed in this paper passive sensors can locate multiple targets at the same time, and the computation burden is moderate.
keywords: {direction-of-arrival estimation;electric sensing devices;statistical analysis;target tracking;3D space;association algorithm;bearing-only measurements;chi-square test;holistic correlation method;multidimension assignment algorithm;nearest-neighbor method;passive sensors;chi-square test;data association;multidimension assignment;passive location},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5367407&isnumber=5367270

Yan Min-xiu, Jing Yuan-wei, He You-guo and Sun Ping, "Adaptive sliding mode controller for a class of second-order underactuated systems," 2009 Chinese Control and Decision Conference, Guilin, 2009, pp. 2782-2786.
doi: 10.1109/CCDC.2009.5194961
Abstract: An adaptive hierarchical sliding-mode control (AHSMC) strategy for a class of second-order underactuated systems is presented. First, the whole system is divided into two subsystems. A first-level sliding surface is defined for each subsystem. Then a second-level sliding surface is defined for these two-level sliding surfaces. The AHSMC law is derived in Lyapunov sense when the uncertainties are bounded by an unknown constant. Therefore, the whole system can be drive to its sliding surface and stable. Finally the simulation results show the validity of the proposed method.
keywords: {Lyapunov methods;adaptive control;control system synthesis;manipulators;variable structure systems;Lyapunov sense;adaptive hierarchical sliding-mode controller design;second-order underactuated systems;underactuated manipulator;Adaptive control;Chemical technology;Control systems;Cranes;Educational institutions;Information science;Orbital robotics;Programmable control;Sliding mode control;Uncertainty;Adaptive Control;Sliding Mode Control;Underactuated System},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5194961&isnumber=5191464

Q. Song, W. Xiong and Y. He, "A track alignment-correlation algorithm with systematic errors in radar network," Radar Conference, 2009 IET International, Guilin, 2009, pp. 1-4.
doi: 10.1049/cp.2009.0408
Abstract: This paper has researched on the problem of track correlation with systematic errors in radar network, and analyzed that how does the systematic errors affect the detected tracks of target theoretically. On the basis, prior to registration, a track alignment-correlation algorithm based on Fourier Transform has been presented. The algorithm estimates the rotation and translation amount by using the Fourier Transform, and aligns the track data of targets reported by radars in the network, can correlate the track accurately without registration, and provide reliable correlated tracks for the next registration.
keywords: {Fourier transforms;correlation methods;radar tracking;Fourier transform;radar network;rotation estimation;systematic errors;track alignment-correlation;Fourier transform;radar network;systematic errors;track correlation},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5367421&isnumber=5367270

Song Jie, He You, Cai Fu-qing and Ge Xian-jun, "New fast methods for moving target detection in non-cooperative bistatic pulse radar," 2008 9th International Conference on Signal Processing, Beijing, 2008, pp. 2457-2460.
doi: 10.1109/ICOSP.2008.4697646
Abstract: According to the characteristics of non-cooperative bistatic pulse radar systems and the issue that the Doppler mismatched loss of the cross-correlation detection of moving targets is serious, two fast methods for joint time delay and Doppler shift estimation of moving targets, based on segment correlation-FFT processing and modified partial segment correlation-FFT processing, are proposed, after analyzing the common methods for cross-ambiguity function processing such as direct calculation, FFT, zoom-FFT method. The processing performance of direct calculation and partial segment correlation-FFT processing of LFM pulse-series is analyzed in theory and by simulation. And the simulation shows that the weak moving target can be detected effectively and the time delay and Doppler shift can be fast estimated by the methods presented in this paper.
keywords: {Doppler shift;fast Fourier transforms;radar detection;Doppler mismatched loss;Doppler shift estimation;LFM pulse-series;cross-ambiguity function processing;cross-correlation detection;moving target detection;noncooperative bistatic pulse radar;segment correlation-FFT processing;zoom-FFT method;Bistatic radar;Delay effects;Delay estimation;Doppler radar;Doppler shift;Helium;Information analysis;Object detection;Radar detection;Signal processing;bistatic radar;doppler shift;moving targets;non-cooperative;time delay},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=4697646&isnumber=4697053

H. Lifang, G. Xin and H. You, "Efficient combination rule of Dezert-Smarandache theory," in Journal of Systems Engineering and Electronics, vol. 19, no. 6, pp. 1139-1144, Dec. 2008.
doi: 10.1016/S1004-4132(08)60210-8
Abstract: The Dezert-Smarandache theory (DSmT) is a useful method for dealing with uncertainty problems. It is more efficient in combining conflicting evidence. Therefore, it has been successfully applied in data fusion and object recognition. However, there exist shortcomings in its combination rule. An efficient combination rule is presented, that is, the evidence's conflicting probability is distributed to every proposition based on remaining the focal elements of conflict. Experiments show that the new combination rule improves the reliability and rationality of the combination results. Although evidences conflict another one highly, good combination results are also obtained.
keywords: {Accuracy;Cognition;Helium;Object recognition;Sensors;Simulation;Uncertainty;DSmT;object recognition;the focal element of conflict},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6072448&isnumber=6072431

Song Jie, He You and Guan Jian, "Development of pulse radar intermediate frequency or video echo signal acquisition system," 2008 Chinese Control and Decision Conference, Yantai, Shandong, 2008, pp. 1617-1621.
doi: 10.1109/CCDC.2008.4597591
Abstract: A portable signal acquisition and recording system is developed, which can be used to acquire pulse radar intermediate frequency or video echo signal. The system uses a laptop as the acquisition control equipment. A radar interface card and a general radar data acquisition card are designed to acquire radar intermediate frequency or video echo signal, which are put into a small shielding box and are very portable. The acquisition card uses USB2.0 as the interface with a microcomputer, uses FPGA as kernel chip to control the data acquisition and data transmission. The system uses FIFO in FPGA, SRAM on acquisition card, multi-thread and buffer storage in microcomputer to provide continuous acquisition, and uses time query and displaying control technique to implement real-time A-scope display on microcomputer monitor. User can set azimuth and distance wave gate of any area, and store acquired data at real time. The data acquisition experiment results show that the system can satisfy the data acquisition tasks of many kinds of radar.
keywords: {data acquisition;field programmable gate arrays;video signal processing;FPGA;data acquisition;general radar data acquisition;kernel chip;pulse radar intermediate frequency;video echo signal acquisition system;Buffer storage;Control equipment;Data acquisition;Field programmable gate arrays;Frequency;Microcomputers;Portable computers;Radar;Signal design;Video recording;FPGA;USB;data acquisition;display;storage},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=4597591&isnumber=4597261

Li Jiu-sheng, Zhao Ji-xiang, He You-feng and Zhou Ye-wen, "Novel RF coupler based on cavity," Microwave and Millimeter Wave Technology, 2008. ICMMT 2008. International Conference on, Nanjing, 2008, pp. 1196-1198.
doi: 10.1109/ICMMT.2008.4540643
Abstract: A compact RF coupler suitable for integrated microwave and millimetre wave applications has been proposed fabricated, and measured for the first time. The novel wideband RF coupler based on cavity offer coupling in the range of 3-10 dB over an ultra-wide frequency band from 700 MHz to 2.5 GHz. The performances of the proposed RF coupler are demonstrated by measured results, which are good agreement with the simulations.
keywords: {UHF couplers;cavity resonators;microwave circuits;millimetre wave circuits;RF coupler based on cavity;frequency 700 MHz to 2.5 GHz;integrated microwave applications;millimetre wave applications;ultra-wide frequency band;wideband RF coupler;Bandwidth;Coupling circuits;Dielectric loss measurement;Dielectric measurements;Dielectric substrates;Helium;Loss measurement;Photography;Radio frequency;Ultra wideband technology},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=4540643&isnumber=4540587

J. Tao, S. Feng, H. You, Q. Changwen and Q. Rongjian, "Optimal Wavelets Vanishing Moments for Singular Signal Detection," Electronic Measurement and Instruments, 2007. ICEMI '07. 8th International Conference on, Xi'an, 2007, pp. 3-782-3-786.
doi: 10.1109/ICEMI.2007.4351034
Abstract: The wavelet transform modular maximum corresponds to the singularity of signal. Based on the fact that wavelet transform modular maximum of signal is different from that of noise at different scales, the noise can be removed from signal. The relationship between wavelet with different vanishing moments and Lipschitz exponent is discussed. And the influence of vanishing moments on singular signal detection is analyzed. The experimental results show that it is necessary to choose appropriate wavelets with different vanishing moments to detect signals with different singularities.
keywords: {signal denoising;signal detection;wavelet transforms;Lipschitz exponent;optimal wavelets vanishing moments;signal denoising;singular signal detection;singularity analysis;Band pass filters;Discrete wavelet transforms;Instruments;Low pass filters;Polynomials;Signal analysis;Signal detection;Signal to noise ratio;Wavelet analysis;Wavelet transforms;Singularity;modular maximum;signal detection;vanishing moments},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=4351034&isnumber=4350397

Z. Li, L. Lingyun and H. You, "New multi-layer data correlation algorithm for multi-passive-sensor location system," in Journal of Systems Engineering and Electronics, vol. 18, no. 4, pp. 667-672, Dec. 2007.
doi: 10.1016/S1004-4132(08)60001-8
Abstract: Under the scenario of dense targets in clutter, a multi-layer optimal data correlation algorithm is proposed. This algorithm eliminates a large number of false location points from the assignment process by rough correlations before we calculate the correlation cost, so it avoids the operations for the target state estimate and the calculation of the correlation cost for the false correlation sets. In the meantime, with the elimination of these points in the rough correlation, the disturbance from the false correlations in the assignment process is decreased, so the data correlation accuracy is improved correspondingly. Complexity analyses of the new multi-layer optimal algorithm and the traditional optimal assignment algorithm are given. Simulation results show that the new algorithm is feasible and effective.
keywords: {Accuracy;Algorithm design and analysis;Complexity theory;Correlation;Heuristic algorithms;Simulation;Size measurement;correlation cost;data correlation;location system;multi layer correlation algorithm;multi passive-sensor},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6071667&isnumber=6071662

Cai Fuqing, Tang Xiaoming and He You, "Research on Bi-static SAR azimuth resolution characteristics," Synthetic Aperture Radar, 2007. APSAR 2007. 1st Asian and Pacific Conference on, Huangshan, 2007, pp. 634-637.
doi: 10.1109/APSAR.2007.4418692
Abstract: In this paper, the problem of Bi-SAR azimuth resolution is studied. Firstly, the three-dimensional bistatic geometrical modal and an approach to azimuth resolution based on gradient are introduced. Then, the main factors influencing Bi-SAR azimuth resolution in practices are analyzed. The computer simulation of the airborne experiment in "tandem" mode tested the validity of the study at the end of the paper. This study is helpful to the Bi-SAR performance analysis and system design.
keywords: {airborne radar;radar resolution;synthetic aperture radar;bi-static SAR azimuth resolution characteristics;synthetic aperture radar;three-dimensional bistatic geometrical modal;Aerospace engineering;Azimuth;Frequency;Helium;History;Receiving antennas;Signal resolution;Transmitters;Transmitting antennas;Vectors;Bi-static Synthetic Aperture Radar (Bi-SAR);azimuth Resolution;vector gradient},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=4418692&isnumber=4418537

Cai Fuqing, He You and Tang Xiaoming, "Research on Bi-static SAR range resolution characteristics," Synthetic Aperture Radar, 2007. APSAR 2007. 1st Asian and Pacific Conference on, Huangshan, 2007, pp. 103-106.
doi: 10.1109/APSAR.2007.4418565
Abstract: In this paper, the problem of Bi-SAR range resolution is studied. Firstly, the physical meaning of Bi-SAR range resolution is analyzed based on the analysis of bistatic radar range resolution characteristics. Then, an approach to Bi-SAR range resolution on the line of receive sight is presented. The analysis of range resolution characteristic of Bi-SAR follows. Detailed simulation tested the validity of the study at the end of the paper.
keywords: {radar resolution;synthetic aperture radar;biSAR systemic design;bistatic SAR range resolution;bistatic radar range resolution;trajectory planning;Aerospace engineering;Bistatic radar;Helium;History;Pulse measurements;Spaceborne radar;Spatial resolution;Synthetic aperture radar;Testing;Transmitters;Bi-static Synthetic Aperture Radar (BiSAR);Range Resolution;Spatial gradient},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=4418565&isnumber=4418537

H. You, X. Wei and M. Qiang, "Composite filtering with feedback information," in Journal of Systems Engineering and Electronics, vol. 18, no. 1, pp. 54-56, March 2007.
doi: 10.1016/S1004-4132(07)60050-4
Abstract: The optimal fusion solution with feedback information for a hybrid multisensor data fusion system is presented. In this system, a part of sensors process their data locally to produce local tracks, and another part of sensors only provide detection reports These tracks and detection reports are communicated to a central site where track fusion and composite filtering are performed. The comparative results on the simulations suggest the feedback information from the center can greatly improve the tracking performance of the local node.
keywords: {Filtering;Noise;Radar tracking;Sensor fusion;Sensor systems;Target tracking;Data fusion;Filtering;Hybrid system;Multisensor tracking},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6071720&isnumber=6071706

G. Xin, Y. Xiao and H. You, "Discretization of Continuous Interval-Valued Attributes in Rough Set Theory and its Application," 2007 International Conference on Machine Learning and Cybernetics, Hong Kong, 2007, pp. 3682-3686.
doi: 10.1109/ICMLC.2007.4370787
Abstract: Rough set theory is a relatively new soft computing tool to deal with vagueness and uncertainty, and is regarded as a field of leading edge. But it cannot deal with continuous attributes, thus discretization is a problem which we cannot neglect. Discretization based on rough set has some particular characteristics, and consistency must be satisfied for discretization of decision systems. Existing discretization methods cannot well process continuous interval-valued attributes in rough set theory. A new approach is proposed to discretize continuous interval-valued attributes in this paper, which enhances the precision of classification and accurate recognition rate in pattern recognition. In the simulation experiment, the decision table was composed of 3 features and 17 radar emitter signals, and the recognition results obtained from this discretization algorithm show that the proposed approach is valid and feasible. The approach expands the application scope of rough set theory.
keywords: {rough set theory;continuous interval-valued attributes;decision systems discretization;pattern recognition;rough set theory;soft computing tool;Aerospace engineering;Cybernetics;Data analysis;Helium;Machine learning;Mathematics;Pattern recognition;Radar;Set theory;Uncertainty;Continuous interval-valued attributes;Discretization;Rough set},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=4370787&isnumber=4370780

C. Lei, H. You and T. Xiao-ming, "Comparison of Distributed and Federated Filtering in Multi-Coordinate Systems," 2006 CIE International Conference on Radar, Shanghai, 2006, pp. 1-4.
doi: 10.1109/ICR.2006.343407
Abstract: Introduce two important equations used in Kalman filter algorithm with coordinates-converting errors. Analyze the characteristic of distributed Kalman filtering algorithm with coordinates converting uncertainties in multi-coordinate sensor systems. Then, an improved federated filtering algorithm is introduced in the same systems. In the new algorithm, local processor can get global optimal estimation by the transformation of measurement equation and coordinate-converting equation. Accordingly, the Kalman filtering algorithm is transformed. Based on these mathematic methods, we only need coordinates converting once to obtain global estimation, which are always needed twice in the distributed algorithms. So, the filtering accuracy is improved. Simulation results also show that the federated algorithm has a better performance in improving the estimation accuracy
keywords: {Kalman filters;sensor fusion;Kalman filter algorithm;coordinates-converting errors;distributed-federated filtering;global optimal estimation;measurement equation;multicoordinate sensor systems;Communication networks;Coordinate measuring machines;Distributed algorithms;Distributed computing;Equations;Filtering algorithms;Information filtering;Information filters;Kalman filters;Uncertainty;coordinates converting errors;data fusion;distributed filtering;federated filtering},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=4148165&isnumber=4118064

H. You, J. Tao, S. Feng and Q. ChangWen, "A method for MTD detectability improvement using FFT/WFFT-DWT," 2006 CIE International Conference on Radar, Shanghai, 2006, pp. 1-4.
doi: 10.1109/ICR.2006.343466
Abstract: When the Doppler frequency of target mismatches the fast Fourier transform (FFT) bin frequencies, the high side lobe appears. Discrete wavelet transform (DWT) has been applied to output of weighed FFT (WFFT) to suppress side lobe. And then FFT/WFFT-DWT is proposed to improve processing gain (PG) further. PG formulae for both WFFT and WFFT-DWT are given. Experimental results demonstrate that FFT/WFFT-DWT can attain much higher detectability than FFT/FFT-DWT as well as FFT in unmatched state
keywords: {fast Fourier transforms;signal detection;Doppler frequency;FFT-WFFT-DWT;MTD;discrete wavelet transform;fast Fourier transform;moving target detector;Additive white noise;Aerospace engineering;Discrete wavelet transforms;Frequency;Gaussian noise;Helium;Noise level;Phase noise;Quantum computing;Radar;Discrete wavelet transform;FFT;MTD;processing gain;signal detection},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=4148467&isnumber=4118064

S. Jie, T. Xiao-ming and H. You, "Muti-Channel Digital LPI Signal Detector," 2006 CIE International Conference on Radar, Shanghai, 2006, pp. 1-4.
doi: 10.1109/ICR.2006.343448
Abstract: The theory of LPI radar signal interception is introduced and a method using multi-channel digital deramping is discussed in detail for FMCW signals. Many simulation experiments on the method have been done in several possible situations, and on the basis of them, the influences of mismatch factor and unsynchronized phase on the detection performance of the digital LPI radar detector are analyzed. At last, the method of estimating the parameters of LPI signal is summarized. It is demonstrated that the LPI radar signal can be extracted from the noise background by means of digital deramping
keywords: {CW radar;FM radar;parameter estimation;radar detection;FMCW signal;LPI radar signal detector;mismatch factor;multichannel digital deramping;parameter estimation;Detectors;Frequency;Phase detection;Radar detection;Radar signal processing;Radar theory;Signal detection;Signal generators;Signal processing;Spread spectrum radar;LPI;chirp signal;digital deramping},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=4148171&isnumber=4118064

G. Xin, Y. Xiao, S. Yingfeng and H. You, "A New Radar Emitter Recognition Method Based on Variable Precision Rough Set Model," 2006 CIE International Conference on Radar, Shanghai, 2006, pp. 1-4.
doi: 10.1109/ICR.2006.343200
Abstract: Radar emitter information detected by multisensor system takes on uncertainty, illegibility and contradiction. In real reconnaissance environment, the patterns of radar classes often overlap, the accurate classification of the Pawlak rough set model restricts its application in the real world. In order to solve emitter recognition problem, a new method of finding decision rules is presented to classify radar emitter from the new point of view of variable precision rough set. This method is according to dependent degree of decision attributes on condition attributes. The decision rules proposed are more straightforward. At last, example of recognizing the radar emitter purposes is selected. During the experiment, discretization is conducted on extracted index data of radar emitter and metrical radar characteristic parameter firstly. Then, positive region of each condition attribute are calculated under the given error parameter, which is the basis of decision rules. Experimental results demonstrate this new radar emitter recognition method by finding decision rules based on variable precision rough set model is effective and feasibility
keywords: {decision theory;radar detection;radar equipment;radar target recognition;rough set theory;sensor fusion;decision rule;extracted index data;metrical radar characteristic parameter;multisensor system;radar detection;radar emitter information;radar emitter recognition method;variable precision rough set model;Aerospace engineering;Databases;Helium;Intelligent sensors;Multisensor systems;Radar applications;Radar detection;Reconnaissance;Sun;Uncertainty;decision rules;radar emitter recognition;variable precision rough set},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=4148306&isnumber=4118064

H. Li, Y. He, R. Yang and J. Guan, "BEAMSPACE BASED DOA ESTIMATION METHODS OF COHERENT SOURCES IN THE PRESENCE OF IMPULSIVE NOISE," 2006 8th international Conference on Signal Processing, Beijing, 2006, pp. .
doi: 10.1109/ICOSP.2006.346127
Abstract: This paper is concerned with the direction of arrival (DOA) estimation of coherent sources in impulse noise fields modeled as symmetric alpha stable (SalphaS) distribution. Robust covariation based MUSIC (ROC-MUSIC) and fractional lower moment based MUSIC (FLOM-MUSIC) cannot be used to estimate the DOA under these conditions. Firstly, new forward-backward smoothing (FBS)-covariation matrices and FBS-FLOM matrices are defined by applying the spatial smoothing idea to covariation matrices and FLOM matrices. Two new algorithms based on FBS-covariation matrices and FBS-FLOM matrices are presented in the meantime. Then, the two algorithms are generalized to beamspace, and other two new algorithms called BROC-SS and BFLOM-SS are proposed. Theoretical analysis shows that noise subspace can be estimated by the eigen-decomposition of covariation matrices and FLOM matrices in both element space and beamspace so as to estimate the DOA of coherent sources in impulse noise. Moreover, performance of four new algorithms is analyzed by comparison. Computer simulation results verify the correctness and effectiveness of the proposed methods
keywords: {covariance matrices;direction-of-arrival estimation;eigenvalues and eigenfunctions;impulse noise;signal classification;beamspace based DOA estimation methods;coherent sources;covariation matrices;direction of arrival;eigen-decomposition;forward-backward smoothing;fractional lower moment matrices;impulsive noise;noise subspace;robust covariation based MUSIC;symmetric alpha stable distribution;1f noise;Additive noise;Aerospace engineering;Computer simulation;Direction of arrival estimation;Helium;Multiple signal classification;Noise robustness;Smoothing methods;Symmetric matrices},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=4129819&isnumber=4129618

H. You, S. Qiang, D. Yun-long and Y. Jian, "Adaptive Tracking Algorithm Based on Modified Strong Tracking Filter," 2006 CIE International Conference on Radar, Shanghai, 2006, pp. 1-4.
doi: 10.1109/ICR.2006.343192
Abstract: The strong tracking filter (STF) can reduce adaptively estimate bias and thus has ability to track maneuvering target in nonlinear systems. However, STF achieves the perfect performance in maneuvering segment at a cost of the precision in non-maneuvering segment. So based on the strong tracking filter, a new adaptive tracking algorithm (modified strong tracking filter, MSTF) is derived in this paper, which is also suitable for tracking maneuvering target and has improved the precision of STF in non-maneuvering segment as well as maneuvering segment. The Monte-Carlo simulation results show that the MSTF algorithm has a more excellent performance than STF and can estimate efficiently
keywords: {Monte Carlo methods;adaptive filters;nonlinear systems;target tracking;tracking filters;MSTF;Monte-Carlo simulation;adaptive tracking algorithm;maneuvering target tracking;modified strong tracking filter;nonlinear system;Adaptive filters;Costs;Covariance matrix;Gaussian noise;Gaussian processes;Nonlinear systems;Robustness;State estimation;Target tracking;White noise;Strong Tracking Filter;extended Kalman filter;target tracking},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=4148298&isnumber=4118064

G. Xin, Y. Xiao and H. You, "A Novel Target Recognition Method Based on Neural Network and Gray Correlation," 2006 8th international Conference on Signal Processing, Beijing, 2006, pp. .
doi: 10.1109/ICOSP.2006.346036
Abstract: In order to solve target recognition problems, D-S reasoning method based on information fusion is applied. The key problem to D-S reasoning is basic probability assignment function, so the algorithm implementation of D-S reasoning is a serious problem. For the special traits of target recognition, a new method of constructing basic probability assignment function based on neural network and gray correlation analysis is presented. Examples of recognizing the radar emitter purpose have been selected to demonstrate the new method. Experimental results show that this information fusion method is accurate and effective
keywords: {inference mechanisms;neural nets;pattern recognition;radar computing;D-S reasoning method;gray correlation analysis;information fusion method;neural network;probability assignment function;radar emitter purpose;target recognition method;Aerospace engineering;Electronic mail;Helium;Neural networks;Parallel processing;Pattern recognition;Probability distribution;Radar;Target recognition;Upper bound},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=4129728&isnumber=4129618

S. Jie, H. You and T. Xiao-ming, "Adaptive Radar Clutter Suppression Based on Real Data," 2006 CIE International Conference on Radar, Shanghai, 2006, pp. 1-4.
doi: 10.1109/ICR.2006.343199
Abstract: Adaptive radar clutter suppression algorithm and realization are important things in radar signal processing system. The paper firstly discusses a method based on the maximum average improvement factor to compute the weight vector of adaptive clutter filter in theory, and then describes a simple, low-cost adaptive MTI system for bimodal clutter suppression, which uses precomputed filter coefficients stored in the weight coefficients library. Results of applying this adaptive MTI filter on real radar data demonstrate that the filter gives an extensive reduction of clutter in the radar image
keywords: {adaptive radar;filtering theory;interference suppression;radar clutter;radar detection;radar imaging;radar target recognition;MTI system;adaptive radar clutter suppression;bimodal clutter suppression;clutter filter;maximum average improvement factor;radar image;radar signal processing system;real data;Adaptive filters;Adaptive systems;Doppler radar;Finite impulse response filter;Frequency estimation;Radar clutter;Radar imaging;Radar signal processing;Signal processing algorithms;Transversal filters;MTI;adaptive filter;clutter suppression},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=4148305&isnumber=4118064

F. Wei, H. You and J. BenQing, "Research and Application on Real-time Acquirement Technique of OpenFlight Digital Terrain Based On Grid," 2006 CIE International Conference on Radar, Shanghai, 2006, pp. 1-4.
doi: 10.1109/ICR.2006.343214
Abstract: Radar system simulation based on digital terrain is a new foreground of radar simulation. However, acquirement of enormous terrain data becomes a difficulty in radar simulation which influences the real time of simulation. The paper analyzes the limitation of structure of openflight digital terrain in radar simulation in detail. A new method for transforming terrain data to grid data is put forward. The method is applied to the design of a certain airborne radar simulation. It is shown that the method successfully solves the problem of digital terrain acquirement and improves the system performance
keywords: {airborne radar;remote sensing by radar;terrain mapping;airborne radar simulation;openflight digital terrain;real-time acquirement technique;Analytical models;Geography;Layout;Radar applications;Radar imaging;Real time systems;Sampling methods;Spatial databases;Virtual reality;Visual databases;Digital terrain;Grid;OpenFlight database;Radar;Radar System Simulation},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=4148320&isnumber=4118064

H. You and Z. Jingwei, "New track correlation algorithms in a multisensor data fusion system," in IEEE Transactions on Aerospace and Electronic Systems, vol. 42, no. 4, pp. 1359-1371, October 2006.
doi: 10.1109/TAES.2006.314577
Abstract: In order to resolve the problem of track-to-track association in a distributed multisensor situation, this paper presents independent and dependent sequential track correlation algorithms based on Singer's and Bar-Shalom's algorithms. Based on sequential track correlation algorithm, the restricted and attenuation memory track correlation algorithms and sequential classic assignment rules are proposed. In this paper, these algorithms are described in detail. Then, the track correlation mass and multivalency processing methods are discussed as well. Finally, simulations are designed to compare the correlation performance of these algorithms with that of Singer's and Bar-Shalom's algorithms. The simulation results show that the performance of these algorithms proposed here is much better than that of the classical methods under the environments of dense targets, interfering, noise, track cross, and so on. Under the above situations, their correct correlation ratio is improved about 69 percent over the classical methods
keywords: {correlation methods;distributed sensors;sensor fusion;Bar-Shalom algorithm;Singer algorithm;attenuation memory;distributed multisensor;multisensor data fusion system;multivalency processing;restricted memory;sequential track correlation;track-to-track association;Aerospace engineering;Attenuation;Covariance matrix;Gaussian noise;Multisensor systems;Noise measurement;Target tracking;Testing;Time measurement;Working environment noise},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=4108006&isnumber=4107974

Guan Xin, Yi Xiao and He You, "Research on unobservability problem for two-dimensional bearings-only target motion analysis," Proceedings of 2005 International Conference on Intelligent Sensing and Information Processing, 2005., 2005, pp. 56-60.
doi: 10.1109/ICISIP.2005.1529420
Abstract: The observability for bearings-only target motion analysis is a very important problem. The bearings-only system is to be said observable if and only if the target motion parameters can be uniquely determined by noise-free bearing measurements. The problem of unobservability for hearing-only target tracking system is discussed in this paper based on the target that travels in the 2-dimentional space with a constant acceleration. Utilizing Gramm rule and rank of matrix, a new proposition that the bearing-only locating and tracking system remains unsolvable prior to an observer maneuver is presented and proved. By proving the proposition, it is shown that for certain type of observer movement the estimation process remains unobservable, even if the target moves with a constant accelerate. The work done in this paper is a valuable study in solving the bearings-only target motion analysis.
keywords: {direction-of-arrival estimation;matrix algebra;observers;position control;target tracking;Gramm rule;estimation process;matrix rule;noise-free bearing measurement;target motion analysis;two-dimensional bearing;unobservability problem;Acceleration;Geometry;Helium;Motion analysis;Observers;Target tracking;Time measurement;Tires;Trajectory;Velocity measurement},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=1529420&isnumber=32656

Z. Li, H. You and Z. Weihua, "Study on data association algorithm of multi-passive-sensor location system," in Journal of Systems Engineering and Electronics, vol. 16, no. 3, pp. 489-493, Sept. 2005.
Abstract: Aiming at three-passive-sensor location system, a generalized 3-dimension (3-D) assignment model is constructed based on property information, and a multi-target programming model is proposed based on direction-finding and property fusion information. The multi-target programming model is transformed into a single target programming problem to resolve, and its data association result is compared with the results which are solved by using one kind of information only. Simulation experiments show the effectiveness of the multi-target programming algorithm with higher data association accuracy and less calculation.
keywords: {Accuracy;Data models;Helium;Mathematical model;Navigation;Programming;Sensors;cost matrix;data association;joint information;programming model},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6071190&isnumber=6071185

Li Hongsheng, He You and Yang Rijie, "A neural blind beamformer for cyclostationary signals," IEEE/ACES International Conference on Wireless Communications and Applied Computational Electromagnetics, 2005., Honolulu, HI, 2005, pp. 345-348.
doi: 10.1109/WCACEM.2005.1469597
Abstract: In this paper a blind beamforming algorithm based on a neural network is presented according to the characteristic of wireless communication signals. This method transforms the question of estimating beamformer weight vectors into the one of computing the SVD of the cross correlation matrix of array input signals and their frequency shift signals. A cross correlation neural network is introduced to compute the SVD of the cross correlation matrix so as to reduce the computational complexity and carry out the blind beamforming more efficiently. The improved cross-coupled Hebbian learning rule presented in this paper can make the weights of the neural network converge much fast. This method can restrain noise and interference. Simulation proves its correctness.
keywords: {Hebbian learning;array signal processing;computational complexity;neural nets;radiocommunication;singular value decomposition;SVD;computational complexity;cross correlation matrix;cross correlation neural network;cross-coupled Hebbian learning rule;cyclostationary signals;frequency shift signals;neural blind beamformer;wireless communication signals;Adaptive signal processing;Array signal processing;Frequency estimation;Hebbian theory;Helium;Interference;Neural networks;Sensor arrays;Signal processing algorithms;Transmission line matrix methods},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=1469597&isnumber=31518

Zhou Li, Guan Jian, He You and Zhang Wei-hua, "Research of multi-dimension assignment algorithm of data association for passive-sensor location system," IEEE International Radar Conference, 2005., 2005, pp. 133-136.
doi: 10.1109/RADAR.2005.1435807
Abstract: Direction-finding cross location algorithm in multi-passive-sensor location systems is a key problem. This paper studies the problem and proposes a modified multi-dimension (S-D) assignment algorithm to solve it. In order to find the global optimal solution, calculation of cost function of all intersection points of passive sensors must be considered, so the calculation burden is heavier. The algorithm proposed in this paper uses a method of passive cross location to eliminate some false intersection points, so that the computation burden of calculating the cost function is decreased. In the meantime, with the removing of the large number of false location points, the effect of data association can be improved compared with the case of calculating the global costs. Simulation results verify the feasibility and validity of the algorithm presented in this paper.
keywords: {direction-of-arrival estimation;sensor fusion;statistics;data association;direction-finding cross location algorithm;multidimension assignment algorithm;multipassive-sensor location systems;Aerospace engineering;Algorithm design and analysis;Computational modeling;Cost function;Educational institutions;Helium;Navigation;Passive radar;Statistics;Vehicle detection},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=1435807&isnumber=30939

He You, Dong Yun-long, Guan Cheng-bin and Wang Guo-hong, "Research on the real-time registration technique for radar networking," 2005 IEEE International Symposium on Microwave, Antenna, Propagation and EMC Technologies for Wireless Communications, Beijing, 2005, pp. 1576-1579 Vol. 2.
doi: 10.1109/MAPE.2005.1618228
Abstract: Since the system errors degrade the association and fusion of the tracks from different radars greatly, registration is the vital problem for the data fusion of the radar network. But the measurements are always nonlinear function of the system biases; therefore, Kalman filter is unable to be used directly two methods are proposed in this paper to solve this problem. First, we use the linear model of literature (M.P Dana, 1990), and present an extended Kalman filter. Second, a sequential Monte Carlo approach is applied to real-time estimation of the state and the system errors, this method is known as particle filtering (M.Sanjeev Arumpalam et al., 2002) also. In the end, simulation results show the effectiveness of the two methods
keywords: {Kalman filters;Monte Carlo methods;nonlinear functions;radar tracking;real-time systems;sensor fusion;data fusion;extended Kalman filter;nonlinear function;particle filtering;radar networking;real-time registration technique;sequential Monte Carlo approach;system error;Argon;Azimuth;Filtering;Noise measurement;Nonlinear filters;Radar tracking;Sensor fusion;Surveillance;Target tracking;Time measurement},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=1618228&isnumber=33908

Gai Ming-jiu, Yi Xiao, He You and Shi Bao, "An approach to tracking a 3D-target with 2D-radar," IEEE International Radar Conference, 2005., 2005, pp. 763-768.
doi: 10.1109/RADAR.2005.1435928
Abstract: Tracking 3D-targets with a 2D-radar is a significant and challenging problem. Motivated by the range-parameterized EKF (RPEKF) algorithm used in the problem of bearing-only tracking, we present a practical solution to solve this problem in this article, i.e., height-parameterized EKF (HPEKF). This method could reduce the fuzzy phenomenon in height information of the target. So we can track 3D-targets with a single 2D-radar in an effective way under some conditions.
keywords: {Kalman filters;filtering theory;radar signal processing;radar tracking;state estimation;target tracking;2D-radar;3D-target tracking;extended Kalman filtering;fuzzy phenomenon;range-parameterized algorithm;state estimation;Aerospace engineering;Covariance matrix;Gaussian noise;Helium;Information filtering;Information filters;Kalman filters;Mathematics;State estimation;Target tracking},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=1435928&isnumber=30939

Xiong wei, Zhang jing-wei and He you, "Multisensor multitarget tracking methods based on particle filter," Proceedings Autonomous Decentralized Systems, 2005. ISADS 2005., 2005, pp. 306-309.
doi: 10.1109/ISADS.2005.1452073
Abstract: In order to solve the multisensor multitarget tracking problem of the non-Gaussian nonlinear systems, the paper presents a multisensor joint probabilistic data association particle (MJPDAP) algorithm. At first, the algorithm permutes and combines the measurement from each sensor using the rule of generalized S-D assignment algorithm. Then, all of measurements in each assignment are combined into one equivalent measurement and the joint likelihood function of the equivalent measurement is calculated. Finally, the particle weight is updated and the state estimation of the fusion center is obtained, using joint probability data association (JPDA) method. In this paper, some Monte Carlo simulations are used to analyze the performance of the new method. The simulation results show the MJPDAP can effectively track multitarget in the nonlinear systems, and be of much better performance than the single-sensor joint probabilistic data association particle (SJPDAP) algorithm.
keywords: {Gaussian processes;Monte Carlo methods;nonlinear systems;probability;sensor fusion;state estimation;target tracking;JPDA;MJPDAP;Monte Carlo simulation;SJPDAP;generalized S-D assignment;joint likelihood function;joint probability data association;multisensor joint probabilistic data association particle;multisensor multitarget tracking;nonGaussian nonlinear system;particle filter;single-sensor joint probabilistic data association particle;state estimation;Helium;Noise measurement;Nonlinear optics;Nonlinear systems;Optical filters;Optical sensors;Particle filters;Particle tracking;State estimation;Time measurement},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=1452073&isnumber=31027

Xiu Jian-juan, Xiu Jian-hua and He You, "Location error analysis of direction finding location system," 2005 IEEE International Symposium on Microwave, Antenna, Propagation and EMC Technologies for Wireless Communications, Beijing, 2005, pp. 1484-1487 Vol. 2.
doi: 10.1109/MAPE.2005.1618206
Abstract: With large detection range, working normally in the condition of electronic countermeasures, direction-finding location systems have attracted great interest of researchers. And a lot of people pay much more attention to passive location technique. But the emphasis of many researchers' work is passive location method, and the location error analysis of multiple passive sensors has received little attention until now. This paper studies the problem, and the minimum ambiguous location area is given. The relationship between the ambiguous location area and the bearing measurements of passive sensors (or the cut angle) is shown in simulation figures, and the positioning error distribution figure is also given. Some conclusions are drawn, which can be used for reference in collocating passive sensors to improve location precision
keywords: {electronic countermeasures;error analysis;military radar;passive radar;radar detection;radio direction-finding;sensor fusion;direction finding location system;electronic countermeasures;location error analysis;multiple passive sensor;Aerospace engineering;Area measurement;Electronic countermeasures;Error analysis;Helium;Navigation;Passive radar;Position measurement;Radar countermeasures;Sensor systems},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=1618206&isnumber=33908

He You, Dong Yunlong, Wang Guohong and Li Dong, "Research on track fusion in radar networking," 2005 IEEE International Symposium on Microwave, Antenna, Propagation and EMC Technologies for Wireless Communications, Beijing, 2005, pp. 334-337 Vol. 1.
doi: 10.1109/MAPE.2005.1617917
Abstract: Distributed multisensor integration methods are always proposed ignored the system errors of the sensors, which degrade the precision of the fusion greatly. In this paper we discussed the influence of the system errors to the precision of the multisensor fusion, and then presented an algorithm based on maximum likelihood model, which can implement fusion and registration altogether. Simulations show that the precision of this method is superior to the original method greatly. Since the system errors are estimated by the maximum likelihood, fusion can also be implement after registration, simulations show the precision of this method is inferior to the maximum likelihood fusion, somewhat
keywords: {maximum likelihood estimation;radar tracking;sensor fusion;distributed multisensor integration methods;maximum likelihood estimation;multisensor fusion;radar networking track fusion;sensor system errors;Aerospace engineering;Azimuth;Equations;Intelligent networks;Maximum likelihood estimation;Radar measurements;Radar tracking;Sensor fusion;Sensor systems;Tellurium},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=1617917&isnumber=33907

L. Hongsheng, H. You and Y. Rijie, "Neural blind beamformer for cyclostationary signals," in Journal of Systems Engineering and Electronics, vol. 16, no. 3, pp. 498-501, Sept. 2005.
doi: 10.1109/WCACEM.2005.1469597
Abstract: A blind beamforming algorithm based on a neural network is presented according to the characteristic of cyclostationary signals. This method transforms the question of estimating beamformer weight vectors into the one of computing the SVD of the cross correlation matrix of array input signals and their frequency shift signals. A cross correlation neural network is introduced to compute the SVD of the cross correlation matrix so as to reduce the computational complexity and carry out the blind beamforming more efficiently. The improved cross-coupled Hebbian learning rule presented can make the weights of the neural network converge much fast. Therefore, it is more promising in the practical use. This method can restrain noise and interference. Simulation proves its correctness.
keywords: {Array signal processing;Arrays;Correlation;Interference;Neural networks;Vectors;blind beamforming;cyclostationarity signals;neural network I;simulation},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6071192&isnumber=6071185

Su Feng, He You and Qu Changwen, "Detecting moving target based on reflectivity displacement method and wavelet transform," IEEE International Radar Conference, 2005., 2005, pp. 487-490.
doi: 10.1109/RADAR.2005.1435875
Abstract: The reflectivity displacement method is one of the generally used methods to detect the moving target in the SAR system. However, in low signal-noise ratio (SNR) environment, it is still difficult to estimate the moving target's parameters correctly. To improve the estimating performance, wavelet transform is adopted as a further processing step to eliminate the noise of graphs obtained from the reflectivity displacement method in this paper. Simulation results demonstrate that it is effective to estimate the parameters of the moving target with the method proposed.
keywords: {parameter estimation;radar signal processing;reflectivity;signal detection;synthetic aperture radar;wavelet transforms;SAR system;moving target detection;parameter estimation;reflectivity displacement method;signal-noise ratio;wavelet transform;Azimuth;Frequency;Pulse compression methods;Radar antennas;Reflectivity;Signal resolution;Signal to noise ratio;Synthetic aperture radar;Wavelet transforms;Working environment noise},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=1435875&isnumber=30939

H. You, D. Yunlong and W. Guohang, "New structure of Kalman filter for radar networking," in Journal of Systems Engineering and Electronics, vol. 16, no. 2, pp. 241-244, June 2005.
Abstract: Due to the different data rates of the sensors and communication delays in the radar netting, the research of the asynchronous multisensor data fusion problem is more practical than that of the synchronous one. Through discussing the sequential approach, which is the classical asynchronous multisensor data fusion algorithm, a new algorithm based on distributed computation structure is proposed. The new algorithm can meet the requirement of real-time computation of netting fusion system, and is more practical for engineering compared with the classical sequential approach. Simulation results show the validity of the presented algorithm.
keywords: {Kalman filters;Radar tracking;Sensor fusion;Target tracking;Time measurement;asynchronous;fusion;multi-sensor;radar networking;sequential},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6071143&isnumber=6071138

Qu Dongcai, Meng Xiangwei, Huang Juan and He You, "Research of artificial neural network intelligent recognition technology assisted by Dempster-Shafer evidence combination theory," Signal Processing, 2004. Proceedings. ICSP '04. 2004 7th International Conference on, 2004, pp. 46-49 vol.1.
doi: 10.1109/ICOSP.2004.1452577
Abstract: The D-S evidence combination theory is another important uncertainty inference method different from information processing by neural network, which is applied widely in intelligent information processing, and highly practical in engineering. On concisely introducing the Dempster-Shafer evidence combination theory frame, this article researches into the neural network intelligent recognition technology assisted by Dempster-Shafter evidence combination theory, sets forth the intelligent recognition tactics, presents the method and procedure of multi-sensor data fusion intelligent recognition on account of the calculating case, and puts forward some questions to be inquired.
keywords: {artificial intelligence;inference mechanisms;neural nets;pattern recognition;sensor fusion;uncertainty handling;Dempster-Shafer evidence combination theory;artificial neural network intelligent recognition technology;intelligent information processing;multisensor data fusion;uncertainty inference method;Artificial intelligence;Artificial neural networks;Information processing;Intelligent networks;Intelligent sensors;Neural networks;Pattern recognition;Sensor fusion;Target recognition;Uncertainty},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=1452577&isnumber=30993

M. Xiangwei, G. Jian and H. You, "Analysis of linear weighted order statistics CFAR algorithm," in Journal of Systems Engineering and Electronics, vol. 15, no. 3, pp. 232-236, Sept. 2004.
Abstract: CFAR technique is widely used in radar targets detection fields. Traditional algorithm is cell averaging (CA), which can give a good detection performance in a relatively ideal environment. Recently, censoring technique is adopted to make the detector perform robustly. Ordered statistic (OS) and trimmed mean (TM) methods are proposed. TM methods treat the reference samples which participate in clutter power estimates equally, but this processing will not realize the effective estimates of clutter power. Therefore, in this paper a quasi best weighted (QBW) order statistics algorithm is presented. In special cases, QBW reduces to CA and the censored mean level detector (CMLD).
keywords: {Algorithm design and analysis;Clutter;Detectors;Helium;Probability;Radar detection;CFAR;detection;order statistics;radar},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6071467&isnumber=6071462

Qu Changwen, He You, Su Feng and Guan Xin, "Application of STFT ridges and RT to moving targets detection in SAR," Microwave and Millimeter Wave Technology, 2004. ICMMT 4th International Conference on, Proceedings, 2004, pp. 669-672.
doi: 10.1109/ICMMT.2004.1411617
Abstract: Synthetic aperture radar (SAR) is an active, all-weather capable system to provide the capability to map the ground with high resolution and is used in both civilian and military applications. Moving targets with respect to the stationary background cause smeared and ill-positioned images. Detection and imaging of moving targets in SAR signals are necessary. We propose the method that combined the ridges of the short-time Fourier transform (STFT) and Radon transform (RT) to detect moving targets. Processing steps of this method and simulated results are given in detail. Simulation results show this method can detect moving targets and estimate its parameters in noise case effectively.
keywords: {Fourier transforms;Radon transforms;radar detection;radar imaging;radar tracking;synthetic aperture radar;Radon transform;SAR signals;moving targets detection;moving targets imaging;short-time Fourier transform ridges;stationary background;synthetic aperture radar;Azimuth;Chirp modulation;Error correction;Fourier transforms;High-resolution imaging;Object detection;Radar antennas;Radar cross section;Radar imaging;Synthetic aperture radar},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=1411617&isnumber=30550

Guan Xin, Yi Xiao and He You, "Bearings-only underwater track fusion solutions with feedback information," Signal Processing, 2004. Proceedings. ICSP '04. 2004 7th International Conference on, 2004, pp. 2449-2452 vol.3.
doi: 10.1109/ICOSP.2004.1442276
Abstract: Considering the characteristics of underwater passive target tracking, the technology of multisensor state estimation in bearings-only underwater distributed system is studied in this paper in order to improve tracking performance. According to feedback mechanism in radar systems, state estimation based on multisensor's bearing sequences is fused on condition that observation platform makes efficient maneuvers. The simulation results show that the track fusion can not only complete the slate estimation but also greatly improve the tracking performance of local sensors by using feedback mechanism. It offers reference to underwater passive target tracking.
keywords: {feedback;passive radar;sensor fusion;sonar signal processing;sonar tracking;state estimation;target tracking;underwater sound;bearings-only underwater distributed system;bearings-only underwater track fusion;feedback information;feedback mechanism;multisensor state estimation;radar system;underwater passive target tracking;Acoustic measurements;Noise measurement;Observers;Sea measurements;Sonar;State estimation;State feedback;Target tracking;Underwater acoustics;Underwater tracking},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=1442276&isnumber=30995

Dong Yunlong, He You and Wang Guohong, "A modified exact maximum likelihood registration algorithm," Computational Electromagnetics and Its Applications, 2004. Proceedings. ICCEA 2004. 2004 3rd International Conference on, 2004, pp. 85-88.
doi: 10.1109/ICCEA.2004.1459295
Abstract: The registration problem is a prerequisite process for radar networking systems to estimate and correct systematic errors accurately. An exact maximum likelihood (EML) registration algorithm was presented in the literature (Zhou Yifeng et al, IEEE Trans. Sigpro., vol.45(6), p.1560-1572, 1997), which incorporates the effects of measurement noise. Although this algorithm is superior to some classical registration algorithms, we find its likelihood function is not exact. A novel modified maximum likelihood (MEML) registration algorithm is presented, which is superior to the EML registration algorithm, with an exact likelihood function. Finally, simulated data are used to evaluate the performance of the two algorithms.
keywords: {maximum likelihood estimation;measurement uncertainty;radar theory;sensor fusion;EML registration algorithm;MEML;exact likelihood function;exact maximum likelihood registration algorithm;measurement noise effects;multisensor fusion;radar networking systems;systematic error correction;Azimuth;Covariance matrix;Density functional theory;Error correction;Helium;Least squares approximation;Maximum likelihood estimation;Noise measurement;Radar;Wide area networks},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=1459295&isnumber=31389

Zhou Li, He You and Dong Yunlong, "Study on three dimension assignment algorithm of radar and ESM data association," Signal Processing, 2004. Proceedings. ICSP '04. 2004 7th International Conference on, 2004, pp. 2001-2004 vol.3.
doi: 10.1109/ICOSP.2004.1442166
Abstract: Among various data association algorithms, the Lagrangian relaxation algorithm of the assignment problem has an advantage in satisfying the association accuracy in application while the calculating speed of this algorithm is not satisfied. This paper presents some studies of the elements that affects the data association of multisensor-multitarget in Lagrangian relaxation algorithm. The effect of data association can be improved through rational modification of the elements involved. Simulation results are given to illustrate the effectiveness of the proposed modification algorithm in this paper.
keywords: {radar signal processing;sensor fusion;ESM data association;Lagrangian relaxation algorithm;radar;three dimension assignment algorithm;Aerospace engineering;Cost function;Educational institutions;Gas detectors;Lagrangian functions;Modems;Numerical simulation;Peak to average power ratio;Radar tracking;Robustness},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=1442166&isnumber=30995

Yi Xiao, Guan Xin and He You, "Multiple models information fusion algorithm for cooperative localization," Signal Processing, 2004. Proceedings. ICSP '04. 2004 7th International Conference on, 2004, pp. 2429-2432 vol.3.
doi: 10.1109/ICOSP.2004.1442271
Abstract: Considerable research has been undertaken in the field of estimation theory in relation to the navigation problem. However, most algorithms are designed for single platform. This paper presents current work on the information fusion problem for multiple platform cooperative navigation. On the basis of the scheme which combines the state prediction and the localization circle, the multiple model (MM) algorithm is introduced to calculate the pseudomeasurement and to update the navigation state. A novel MM-based cooperative localization algorithm is presented. The importance of the new approach is that the performance is greatly improved while the alignment of different localization circles is not necessary too.
keywords: {estimation theory;navigation;sensor fusion;MM-based cooperative localization algorithm;estimation theory;localization circle;multiple model algorithm;multiple models information fusion algorithm;multiple platform cooperative navigation;state prediction;Aerospace engineering;Algorithm design and analysis;Covariance matrix;Estimation theory;Gaussian noise;Helium;Motion planning;Navigation;Predictive models;Target tracking},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=1442271&isnumber=30995

Xiu Jian-juan, He You and Che Zhi-yu, "Three-dimensional passive location algorithm of the OTHT [over-the-horizon target]," Computational Electromagnetics and Its Applications, 2004. Proceedings. ICCEA 2004. 2004 3rd International Conference on, 2004, pp. 360-363.
doi: 10.1109/ICCEA.2004.1459366
Abstract: Three dimensional passive location and tracking of the over-the-horizon target (OTHT) is a key problem in recent years. It can influence the long-distance detection, location and precision attack capability of military equipment. So This work studies the problem, and presents a new method, which uses active tracking technology and a time difference of arrival (TDOA) location method to track the OTHT. Simulation results show that the over-the-horizon target can be located and tracked by the method proposed In this work.
keywords: {military radar;radar detection;radar signal processing;target tracking;time-of-arrival estimation;3D passive location algorithm;OTHT tracking;TDOA location method;active tracking technology;hyperbolic location method;long-distance detection;military equipment attack capability;military radar systems;over-the-horizon target tracking;time difference of arrival location method;tracking location;Electromagnetic measurements;Electronic countermeasures;Helium;Passive radar;Radar countermeasures;Radar tracking;Satellite ground stations;Target tracking;Time measurement;Transmitters},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=1459366&isnumber=31389

He You, Su Feng and Qu Changwen, "A novel multiple LFM signals detection method," Microwave and Millimeter Wave Technology, 2004. ICMMT 4th International Conference on, Proceedings, 2004, pp. 818-821.
doi: 10.1109/ICMMT.2004.1411655
Abstract: The Wigner-Ville distribution (WVD) Hough transform could effectively detect several linear-frequency modulated (LFM) signals in low signal-noise ratio (SNR) environment. However, when the energy of these LFM signals diverge greatly, it is quite difficult to detect all LFM signals with the WVD-Hough transform at the same time, because the platform of strong signals will cover weak signals. All LFM signals can be detected with the "CLEAN" technique, but this solution can only be achieved at the cost of a large increase in computational load. In this paper, a signal detection method based on WVD and binary integration in Hough transform parameter space is proposed according to the WVD-Hough transform. Using this method, strong signals as well as the weak signals covered by the strong signals could be detected simultaneously. It means that this method has high practicable value. Simulation results verify the effectiveness of this method.
keywords: {Hough transforms;Wigner distribution;frequency modulation;signal detection;Hough transform;Wigner-Ville distribution;binary integration;linear-frequency modulated signals;multiple LFM signals detection;signal strength;Amplitude modulation;Chirp modulation;Costs;Energy resolution;Gaussian noise;Shape;Signal detection;Signal resolution;Time frequency analysis},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=1411655&isnumber=30550

Meng Xiangwei, Guo Haiyan and He You, "The best linear unbiased with greatest of selection (BLUGO) CFAR algorithms," Aerospace Conference, 2004. Proceedings. 2004 IEEE, 2004, pp. 1985 Vol.3.
doi: 10.1109/AERO.2004.1367980
Abstract: This work presents a new CFAR detector with greatest of selection based on best linear unbiased method (BLUGO-CFAR). This CFAR detector has the ability of CFAR algorithms with greatest of selection to control the rise of false alarm rate at clutter edge, it also has the advantage of CFAR algorithms based on order statistics in multiple targets situation. The analytic results show that the performance of BLUGO is evidently superior to that of OSGO both in homogeneous background and in multiple targets situations, resulting by an increase in the number of order statistics to estimate the noise power level. Since the reference window is split into two sub-windows, the sample sorting time is reduced as half as that of OS. If Ml=M2=0, Nl=N2=0, BLUGO reduces to GO, if M1=N1=O, BLUGO reduces to MX-CMLD.
keywords: {signal detection;statistical analysis;target tracking;CFAR detector;best linear unbiased method;clutter edge;false alarm rate;homogeneous background;multiple targets situation;noise power level;order statistics;reference window;sorting time;Aerospace engineering;Cities and towns;Degradation;Detectors;Erbium;Helium;Performance analysis;Radar clutter;Roads;Testing},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=1367980&isnumber=29902

Xia Mingge, He You, Huang Xiaodong and Su Feng, "Image fusion algorithm using rough sets theory and wavelet analysis," Signal Processing, 2004. Proceedings. ICSP '04. 2004 7th International Conference on, 2004, pp. 1041-1044 vol.2.
doi: 10.1109/ICOSP.2004.1441500
Abstract: Wavelets with their multiresolution property, have been proved to be effective in the integrating of the coarse features and finer resolution details of source images to produce a good fused image. The theory of rough sets has emerged as a major mathematical approach for managing uncertainty that arises from inexact, noisy, or incomplete information. Image fusion algorithm using rough sets and wavelet analysis is proposed in this paper. Multifocus images are enhanced using rough sets, then fused them using Db4 wavelet. The proposed fusion scheme is examined on images which are contaminated by salt-pepper noise. Entropy is used to evaluate image quality. Experimental results demonstrate the effectiveness of the image fusion algorithm.
keywords: {feature extraction;image enhancement;image resolution;rough set theory;wavelet transforms;Db4 wavelet analysis;coarse feature integration;entropy;finer resolution detail;image fusion algorithm;image quality evaluation;multifocus image enhancement;multiresolution property;rough set theory;salt-pepper noise contamination;Aerospace engineering;Algorithm design and analysis;Filter bank;Helium;Image analysis;Image fusion;Image resolution;Low pass filters;Rough sets;Wavelet analysis},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=1441500&isnumber=30994

Guan Xin, He You and Yi Xiao, "A novel gray model for radar emitter recognition," Signal Processing, 2004. Proceedings. ICSP '04. 2004 7th International Conference on, 2004, pp. 2116-2119 vol.3.
doi: 10.1109/ICOSP.2004.1442193
Abstract: Based on radar practical reconnaissance environment, the application of gray correlation analysis method in emitter recognition is deeply studied in this paper. Firstly, the detailed steps of the method are put forward. Secondly, two approaches to determining the weighed coefficients are also proposed, which overcome the subjectivity in traditional ones. Thirdly, the recognition criterion is discussed. On the base of which, the radar emitter recognition of model and mode are conducted. It can be used for radar emitter whose measurement parameters are incomplete. The simulation results show the feasibility and validity of the novel approach.
keywords: {correlation methods;radar signal processing;gray correlation analysis method;gray model;radar emitter recognition;Aerospace engineering;Analytical models;Electronic warfare;Libraries;Mathematics;Radar detection;Radar measurements;Radio frequency;Reconnaissance;Space vector pulse width modulation},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=1442193&isnumber=30995

Dong Yunlong, He You and Wang Guohong, "A generalized least squares registration algorithm with Earth-centered Earth-fixed (ECEF) coordinate system [radar sensor fusion applications]," Computational Electromagnetics and Its Applications, 2004. Proceedings. ICCEA 2004. 2004 3rd International Conference on, 2004, pp. 79-84.
doi: 10.1109/ICCEA.2004.1459294
Abstract: The registration problem is a prerequisite process for radar networking systems to estimate and correct systematic errors accurately. Some classical registration algorithms are all based on stereographic projection, which introduces errors to the registration of the long distance sensors. We present a generalized least squares registration algorithm (ECEF-GLS) in an Earth-centered Earth-fixed coordinate system. The new approach solves the registration between the long distance sensors, and the covariance of the estimation achieves the Cramer-Rao bound (CRLB), ignoring the errors of the linear model. Simulated data are used to evaluate the performance of the proposed algorithm. Comparisons are made to the ECEF-LS algorithms proposed by Zhou.
keywords: {error analysis;least squares approximations;radar theory;sensor fusion;Cramer-Rao bound;ECEF-GLS;Earth-centered Earth-fixed coordinate system;error analysis;generalized least squares registration algorithm;least squares estimation covariance;long distance sensors;multisensor fusion;radar networking systems;systematic error correction;Azimuth;Earth;Error correction;Helium;Least squares approximation;Least squares methods;Maximum likelihood estimation;Quality control;Radar;Uncertainty},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=1459294&isnumber=31389

Yi Xiao, He You and Guan Xin, "Cooperative location model under the Nearest Neighbor criterion," Position Location and Navigation Symposium, 2004. PLANS 2004, 2004, pp. 658-661.
doi: 10.1109/PLANS.2004.1309056
Abstract: This paper presents current work on decentralized data fusion applied to the relative localization among multiple platform, which is one of the key formation control techniques for mobile robots or unmanned aerial vehicles. A novel Nearest Neighbor-based scheme is proposed to estimate the navigational states own from the range measurement to other platform. The model to calculate the pseudomeasurement and the concomitant error covariance matrix is deduced for the planar circumstance.
keywords: {navigation;position measurement;sensor fusion;Nearest Neighbor criterion;cooperative location model;decentralized data fusion;error covariance matrix;formation control techniques;mobile robots;multiple platform;planar circumstance;relative localization;unmanned aerial vehicles;Covariance matrix;Helium;Kinematics;Mobile robots;Navigation;Nearest neighbor searches;State estimation;Target tracking;Time division multiple access;Unmanned aerial vehicles},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=1309056&isnumber=29049

Y. Rijie, He You, Zhang Xin and Cui Xutao, "The method research for reconstructing the modulation spectrum of radiant noises based on iterative algorithm," Computational Electromagnetics and Its Applications, 2004. Proceedings. ICCEA 2004. 2004 3rd International Conference on, 2004, pp. 537-540.
doi: 10.1109/ICCEA.2004.1459411
Abstract: In order to research the propagation characteristics of radiant noise in a sound field, the line spectrum, the continuous spectrum and the modulation spectrum, which contain the target's characteristic and can be obtained by means of filtering and characteristics extraction, are expected to reconstruct radiant noise in the simulation for radiant noise signals. An algorithm suitable for estimating the modulation depth spectrum, which utilizes the iterative algorithm, is presented. The reconstructed model of time domain radiant noise is provided in this paper. The time domain signals of measured data are reconstructed from the starting point of the modulation spectrum, before and after reconstructing; the modulation spectrum's error is analyzed.
keywords: {acoustic noise;acoustic signal processing;acoustic wave propagation;iterative methods;modulation;signal reconstruction;spectral analysis;continuous spectrum;error analysis;iterative algorithm;line spectrum;modulation depth spectrum;modulation spectrum reconstruction;propagation characteristics;radiant noise;sound field;Acoustic noise;Acoustic propagation;Aerospace engineering;Blades;Image reconstruction;Iterative algorithms;Noise measurement;Rhythm;Time domain analysis;Time measurement},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=1459411&isnumber=31389

Xiu Jian-juan, He You and Xiu Jianhua, "Bearing measurements association algorithm in passive location system," Computational Electromagnetics and Its Applications, 2004. Proceedings. ICCEA 2004. 2004 3rd International Conference on, 2004, pp. 356-359.
doi: 10.1109/ICCEA.2004.1459365
Abstract: This work studies the multitarget passive location and tracking problem of multiple passive sensors. Since bearing only location of the multisensors will produce a lot of false intersection points in dense environments. In order to eliminate these false intersection points correctly and quickly, a two-level bearing measurement association algorithm is proposed In this work. This method firstly uses a rule to eliminate some false intersection points, so the computation burden is decreased. Then, the maximum likelihood algorithm is used to associate the bearing measurements, which can ensure the true association rate is high. Simulation is also made, and the results reveal the feasibility and validity of the bearing measurements association algorithm presented In this work, and multiple targets can be located and tracked at the same time by passive sensors.
keywords: {direction-of-arrival estimation;maximum likelihood estimation;radar signal processing;sensor fusion;target tracking;association rate;bearing measurements association algorithm;false intersection point elimination;maximum likelihood algorithm;multiple passive sensors;multisensor bearing-only location information;multitarget passive location system;target tracking;Covariance matrix;Gaussian noise;Noise measurement;Read only memory;White noise},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=1459365&isnumber=31389

Qu Changwen, Huang Yong, Su Feng and He You, "Performance analysis of a Hough-based TBD algorithm using Pade approximations," Microwave and Millimeter Wave Technology, 2004. ICMMT 4th International Conference on, Proceedings, 2004, pp. 879-882.
doi: 10.1109/ICMMT.2004.1411671
Abstract: In the background of K-clutter plus thermal noise, the performance of track-before-detect (TBD) algorithm based on Hough transform is analyzed detailed and the analytical expressions of detection probability and false-alarm probability are given. Then the Pade approximation (PA) method is used to approximately calculate these analytical expressions, which avoids complicated integral computation and conveniently finishes evaluating the detection performance. Lastly Monte Carlo simulation shows the feasibility of Pade approximations.
keywords: {Hough transforms;approximation theory;probability;signal detection;thermal noise;Hough transform;Monte Carlo simulation;Pade approximations;analytical expressions;detection probability;false-alarm probability;performance analysis;thermal noise;track-before-detect algorithm;Aerospace engineering;Algorithm design and analysis;Helium;Noise level;Noise shaping;Performance analysis;Probability;Radar detection;Radar tracking;Spaceborne radar},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=1411671&isnumber=30550

Meng Xiangwei, Guan Jian and He You, "A modified quasi-best weighted order statistics CFAR algorithm with greatest of selection," Neural Networks and Signal Processing, 2003. Proceedings of the 2003 International Conference on, Nanjing, 2003, pp. 860-863 Vol.1.
doi: 10.1109/ICNNSP.2003.1279412
Abstract: In order to improve the performance of OSGO or GOSGO, a CFAR algorithm based on quasi best weighted (QBW) order statistics CFAR method is proposed in this paper. The analytic results show that the performance of QBWGO is evidently superior to that of OSGO or GOSGO both in a homogeneous background and in multiple target situations. If the number of interfering targets is 4, the CFAR loss of QBWGO is 4.659, the CFAR loss of OSGO is 5.357, and an improvement of nearly 1 dB by QBWGO is obtained. In the special case of M/sub 1/=M/sub 2/=0, N/sub 1/=N/sub 2/=0, QBWGO reduces to GO, and in the case of M/sub 1/=N/sub 1/=0, QBWGO reduces to MX-CMLD.
keywords: {matched filters;radar detection;radar target recognition;statistical analysis;OSGO;cell-average CFAR detector;generalized OSGO;interfering targets;multiple target situations;quasi-best weighted order statistics;quasi-best weighted order statistics CFAR algorithm;radar target detection;Aerospace engineering;Cities and towns;Clutter;Envelope detectors;Erbium;Helium;Radar detection;Roads;Statistics;Testing},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=1279412&isnumber=28596

Meng Xiangwei, Guan Jian and He You, "CFAR techniques for over-the-horizon radar," Intelligent Signal Processing, 2003 IEEE International Symposium on, 2003, pp. 83-85.
doi: 10.1109/ISP.2003.1275818
Abstract: Since the OTHR background noise is too strong, the target echoes would be embedded in sea clutter and environment noise. In order to detect targets such as ships or aircrafts from radar returns, a range Doppler CFAR schemes is presented, the identical Doppler frequency resolution cells over adjacent range or azimuth resolution cells are used to form a sliding window for targets detection. Since the OTHR range resolution cells is very large and so do the azimuth resolution cells, the total number of range Doppler resolution cells that forms sliding window is limited in order to guarantee stationary. Some CFAR algorithms such as CA, CM, TM, BLU and QBW methods that are suitable for OTHR are compared and analyzed versus different total range or azimuth resolution cells number. If the total range Doppler resolution cells number is small (less than 12), CA-CFAR is preferred in order to get the good detection performance. In multiple targets situation, CM-CFAR or TM-CFAR are suggested which trims the largest samples that possibly be interfering targets.
keywords: {Doppler radar;military radar;radar clutter;radar detection;radar resolution;statistical analysis;target tracking;CFAR algorithms;CFAR techniques;Doppler CFAR schemes;Doppler frequency resolution cells;azimuth resolution cells;constant false alarm rate;over the-horizon radar;sea clutter;target detection;Airborne radar;Aircraft;Azimuth;Background noise;Clutter;Doppler radar;Frequency;Marine vehicles;Radar detection;Working environment noise},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=1275818&isnumber=28530

T. Xiaoming, H. You and W. Guohong, "A new deghosting algorithm with hypothesis testing data fusion," in Journal of Systems Engineering and Electronics, vol. 14, no. 2, pp. 14-19, June 2003.
Abstract: Eliminating the false intersection (deghosting) is a difficult problem in a passive cross location system. Using a decentralized decision fusion topology, a new deghosting algorithm derived from hypothesis testing theory is developed. It uses the difference between ghosts and true targets in the statistical error, which occurs between their projection angles on a deghosting sensor and is measured from a deghosting sensor, and constructs a corresponding test statistic. Under the Gaussian assumption, ghosts and true targets are decided and discriminated by Chi-square distribution. Simulation results show the feasibility of the algorithm.
keywords: {Estimation;Helium;Measurement uncertainty;Simulation;Testing;Topology;Vectors;Decentralized decision fusion;Deghosting;Hypothesis testing},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6077498&isnumber=6077492

Meng Xiangwei, Guan Jian and He You, "A generalized smallest of selection CFAR algorithm [radar signal processing]," Radar Conference, 2003. Proceedings of the International, 2003, pp. 130-132.
doi: 10.1109/RADAR.2003.1278724
Abstract: A generalized smallest of selection CFAR (constant false alarm rate detection) algorithm (TMSO), based on the trimmed mean (TM) method, is proposed in this paper. It takes the smallest local estimation of either the leading or lagging window, which applies the trimmed mean method as a noise power estimation to set an adaptive threshold. Thus, the smallest of selection (SO), the generalized ordered statistic smallest of (GOSSO), or the ordered statistic smallest of (OSSO), is the special case of TMSO. It is shown that the performance of TMSO in homogeneous background and in multiple target situations is improved over that of GOSSO or OSSO.
keywords: {adaptive signal processing;radar detection;radar signal processing;GOSSO;OSSO;TMSO;adaptive threshold;constant false alarm rate detection;generalized ordered statistic smallest of method;generalized smallest of selection CFAR algorithm;homogeneous background;lagging window local estimation;leading window local estimation;multiple targets;noise power estimation;radar detection environment;trimmed mean method;Aerospace engineering;Cities and towns;Degradation;Envelope detectors;Erbium;Helium;Radar detection;Roads;Statistics;Testing},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=1278724&isnumber=28560

H. You and X. Wei, "Relationship between track fusion solutions with and without feedback information," in Journal of Systems Engineering and Electronics, vol. 14, no. 2, pp. 47-51, June 2003.
Abstract: In distributed multisensor data fusion systems, there are two types of track fusion approaches. One is sensor track fusion with feedback information, the other is without feedback information. This paper proves that the solutions of sensor track fusion with and without feedback information are both optimal and equal.
keywords: {Educational institutions;Estimation;Helium;Noise;Radar tracking;Target tracking;Vectors;Data fusion;Feedback;Multisensor},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6077503&isnumber=6077492

Guan Jian, Meng Xiang-Wei and He You, "Distributed CFAR detection with multisensor using local multilevel quantization based on rank [radar detection]," Radar Conference, 2003. Proceedings of the International, 2003, pp. 127-129.
doi: 10.1109/RADAR.2003.1278723
Abstract: This paper proposes a multilevel quantization algorithm based on rank and applies it as local processing algorithm to the distributed CFAR (constant false alarm rate) detection with multisensors in a parallel topology. An analytical expression of its performance is derived. A comparison is made with the scheme based on local binary quantization. Result shows that even if without optimization, the new scheme also obtains obvious performance improvements over the distributed detection based on local binary quantization and optimal fusion.
keywords: {distributed sensors;quantisation (signal);radar detection;radar signal processing;constant false alarm rate detection;distributed CFAR detection;local binary quantization;multilevel local quantization algorithm;parallel topology multisensors;rank based local multilevel quantization;Aerospace engineering;Circuit topology;Cities and towns;Clutter;Density functional theory;Helium;Multisensor systems;Performance analysis;Quantization;Testing},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=1278723&isnumber=28560

Meng Xiangwei, Guan Jian and He You, "Performance analysis of the weighted window CFAR algorithms [radar signal processing]," Radar Conference, 2003. Proceedings of the International, 2003, pp. 354-357.
doi: 10.1109/RADAR.2003.1278766
Abstract: With the deterioration of radar operation environment and the enhancement of menace to radar, the task of radar target detection becomes more complicated. Such as the detection of airplane, ship or cruise missile in over the horizon radar (OTHR), and the detection of moving targets in synthetic aperture radar (SAR). Therefore, it is necessary to make a further study of CFAR algorithms. The performance of the conventional cell averaging (CA) algorithm is the best in a homogeneous background since it uses the maximum likelihood estimate of the noise power to set the adaptive threshold. But if the interfering target is present in the reference window with a target return in the test cell, severe masking of targets appears due to increased threshold. In order to overcome this problem, the ordered statistic (OS) and the trimmed mean (TM) algorithms, using a trimmed technique, are proposed. If the reference sample number is not too big, the CFAR loss of OS and TM increase greatly. This case can usually be encountered in a complicated environment and lower SNR situation. In this paper, a weighted window techniques such as rectangle, stepped and trapezium windows are discussed. The analysis results show that the weighted window technique can greatly improve in a homogeneous background and obtain an immune ability to interfering targets to some extent.
keywords: {adaptive signal processing;radar detection;radar signal processing;synthetic aperture radar;OTHR;SAR;adaptive threshold;airplane;cruise missile;interfering targets immune ability;moving targets;ordered statistic algorithm;over the horizon radar;radar menace;radar operation environment deterioration;radar target detection;rectangle windows;ship;stepped windows;synthetic aperture radar;trapezium windows;trimmed mean algorithm;weighted window CFAR algorithms;Airborne radar;Airplanes;Marine vehicles;Missiles;Object detection;Performance analysis;Radar detection;Radar signal processing;Signal processing algorithms;Synthetic aperture radar},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=1278766&isnumber=28560

Tang Xiaoming, He You, Dong Shijia and Ni jinlin, "Doppler compensation for passive coherent location," Signal Processing, 2002 6th International Conference on, 2002, pp. 1457-1460 vol.2.
doi: 10.1109/ICOSP.2002.1180068
Abstract: For target movement without velocity information in a passive coherent location system, the unknown Doppler shift between the direct signal and the target echo results in a decrease of the highest peak output value and the occurrence of some false peaks. Several Doppler compensation methods are compared in terms of the Doppler decorrelation loss factor. The Doppler decorrelation loss from the different inherent correlation times of signals and the different overlap times in the cross-correlator is analyzed. Simultaneously, the rationality of two stage processing is explained. In order to reduce the computational burden much more, an FFT pruning algorithm is introduced into segment Doppler compensation. The results of simulations are in close agreement with theory predictions.
keywords: {Doppler shift;decorrelation;fast Fourier transforms;search radar;Doppler compensation;Doppler decorrelation loss factor;Doppler shift;FFT pruning algorithm;broad area surveillance;computational burden;cross-correlator;inherent correlation time;overlap time;passive coherent location system;target movement;Aerospace engineering;Computational modeling;Decorrelation;Doppler shift;Frequency;Helium;Signal analysis;Signal processing;Signal to noise ratio;Surveillance},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=1180068&isnumber=26504

Qu Changwen and He You, "A method of threat assessment using multiple attribute decision making," Signal Processing, 2002 6th International Conference on, 2002, pp. 1091-1095 vol.2.
doi: 10.1109/ICOSP.2002.1179979
Abstract: Threat assessment as high level data fusion has received significant attention for military application. The expert systems technique is often applied to threat assessment. Decision making is a reasoning procedure and suitable for threat assessment. According to the characteristics of the threat assessment and multiple attribute decision making, a method for threat assessment based on multiple attribute decision making is presented in this paper. Fuzzy membership functions and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) are used in this method. This method is easy to implement in practice and good at real-time processing.
keywords: {decision making;expert systems;fuzzy logic;military computing;real-time systems;sensor fusion;TOPSIS;Technique for Order Preference by Similarity to Ideal Solution;expert systems;fuzzy membership functions;high level data fusion;military application;multiple attribute decision making;real-time processing;reasoning;threat assessment;Aerospace engineering;Command and control systems;Communication system control;Decision making;Expert systems;Fuzzy set theory;Helium;Intelligent sensors;Military communication;Real time systems},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=1179979&isnumber=26504

Xiu Jianjuan, He You, Xiu Jianhua and Wang Guohong, "Passive location algorithm of two sensors based on multihypothesis extended Kalman filter," Signal Processing, 2002 6th International Conference on, 2002, pp. 1411-1414 vol.2.
doi: 10.1109/ICOSP.2002.1180057
Abstract: Multitarget tracking with bearings only measurements of two passive sensors is a very important problem, which has not been solved. To counter this problem a method is proposed in this paper, This method firstly used the bearing measurements of two passive sensors to estimate the initial range interval of targets, which are divided into several subintervals. At each subinterval an extended Kalman filter and a multihypothesis method are used to estimate the state of targets. At the same time the bearing measurements are associated. Combined state estimate is obtained as weighted sums of the state estimate of each subinterval. Simulation results show that through using the algorithm discussed in this paper two passive sensors can locate and track multiple targets at the same time.
keywords: {Kalman filters;antenna arrays;array signal processing;military radar;radar antennas;radar tracking;receiving antennas;target tracking;bearings only measurements;combined state estimate;extended Kalman filter;multihypothesis extended Kalman filter;multihypothesis method;multitarget tracking;passive location algorithm;passive sensors;subinterval;Aerospace engineering;Auditory system;Counting circuits;Helium;Position measurement;Radar tracking;State estimation;Target tracking;Time measurement;Vehicles},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=1180057&isnumber=26504

Guan Jian, Meng Xiang-Wei, Peng Ying-Ning and He You, "The optimality in Neyman-Pearson sense in the distributed CFAR detection with multisensor," Radar Conference, 2002. Proceedings of the IEEE, 2002, pp. 68-72.
doi: 10.1109/NRC.2002.999695
Abstract: The optimality in Neyman-Pearson (NP) sense in distributed CFAR detection with multisensor is discussed. Most of the existing analysis of optimization of distributed CFAR detection in the NP sense is done under the limitation of binary local decision and no communication among local processors. We find that the real optimization in the NP sense can not be realized under this limitation. If local test statistics (LTS) are used and fused, the real optimal NP test could be implemented by likelihood ratio test (LRT).
keywords: {optimisation;sensor fusion;signal detection;statistical analysis;Neyman-Pearson optimality;binary local decision;distributed CFAR detection;likelihood ratio test;local test statistics;multisensor;optimal NP test;optimization;Aerospace engineering;Background noise;Detectors;Helium;Light rail systems;Probability;Statistical analysis;Statistical distributions;Testing;Topology},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=999695&isnumber=21572

He You, Huang Xiaodong and Ren Shaolong, "A distributed track correlation algorithm based on multi-elements fuzzy synthetic decision," Radar, 2001 CIE International Conference on, Proceedings, Beijing, 2001, pp. 728-731.
doi: 10.1109/ICR.2001.984818
Abstract: A distributed track correlation algorithm based on multi-element fuzzy synthetic decision, and its correlation criteria are presented. The algorithm is also compared with the two classic algorithms through simulations. The results of simulations show that the performance of the algorithm presented in this paper is more perfect than the classic ones, especially under dense targets, track crossing and target maneuvering environments, and the rate of correct correlation improves about 37 percent
keywords: {correlation methods;distributed algorithms;fuzzy set theory;radar tracking;target tracking;correlation criteria;dense targets;distributed track correlation algorithm;multi-element fuzzy synthetic decision;performance;target maneuvering;track crossing;Aerospace engineering;Clutter;Delay;Fuzzy sets;Helium;Interference;Sensor fusion;Sensor phenomena and characterization;Target tracking;Working environment noise},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=984818&isnumber=21220

Guan Jian, He You, Peng Ying-Ning and Meng Xiang-Wei, "Study of centralized CFAR detection with multisensor," Radar, 2001 CIE International Conference on, Proceedings, Beijing, 2001, pp. 334-337.
doi: 10.1109/ICR.2001.984685
Abstract: The centralized constant false alarm rate (CFAR) detection with multiple non-like sensors is studied in nonhomogeneous background. Results show that the centralized processing for CFAR detection with multiple non-like sensors is heavily affected by the variation of the relative ratio of local clutter power levels. The remedies are given
keywords: {radar clutter;radar detection;radar signal processing;statistical analysis;Rayleigh distribution;centralized CFAR detection;centralized processing;local clutter power levels;multisensor;nonhomogeneous background;radar clutter;Aerospace engineering;Background noise;Clutter;Envelope detectors;Exponential distribution;Helium;Interference;Signal analysis;Signal to noise ratio;Testing},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=984685&isnumber=21220

Xiu Jianjuan, He You, Xiu Jianhua and Yan Hongxing, "Study on multitarget tracking algorithm in passive cross location systems," Radar, 2001 CIE International Conference on, Proceedings, Beijing, 2001, pp. 1119-1123.
doi: 10.1109/ICR.2001.984907
Abstract: When the coordinates of the target are obtained by direction-finding location through multiple passive sensors, the associated bearing measurements must be the same time detection of these sensors. But these sensors may have different sampling intervals, and the time of these sensors beginning to receive the target signal may be also different. In this case, the first problem one must solve in direction-finding location is measurement synchronization. The paper studies this problem and proposes a method to solve it. An improved least distance method is used in this paper to eliminate the false intersection points. The methods of track initiation and maintenance in multitarget tracking are also discussed in this paper. The simulation results show that passive sensors can track multiple targets at the same time using the methods discussed in this paper
keywords: {direction-of-arrival estimation;military radar;radar antennas;radar signal processing;radar tracking;signal sampling;synchronisation;target tracking;bearing measurements;direction-finding location;false intersection points;least distance method;measurement synchronization;multiple passive sensors;multitarget tracking;passive cross location systems;radar antennas;sampling intervals;time detection;track initiation;track maintenance;Aerospace engineering;Azimuth;Coordinate measuring machines;Extraterrestrial measurements;Goniometers;Helium;Navigation;Sampling methods;Target tracking;Time measurement},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=984907&isnumber=21220

Ren Shao-Long, He You and Xiong Wei, "State estimation with feedback information in a hybrid multisensor system," Radar, 2001 CIE International Conference on, Proceedings, Beijing, 2001, pp. 723-727.
doi: 10.1109/ICR.2001.984817
Abstract: In order to improve the tracking performance of sensors, this paper addresses the issue of optimal state estimation in a hybrid multisensor data fusion system with feedback information for similar and dissimilar synchronous sensors. In this system, part of the sensors process their data locally to produce local tracks while another part of the sensors only provide detection reports. These tracks and detection reports are communicated to a central site where track fusion and state estimation are performed. The fusion results are then returned to some sensors, so that the tracking performance of the sensors might be improved
keywords: {Kalman filters;feedback;filtering theory;radar signal processing;radar tracking;sensor fusion;state estimation;Kalman filter;central communication site;detection reports;dissimilar synchronous sensors;feedback information;hybrid multisensor data fusion system;local data processing;local tracks;multicoordinate systems;optimal state estimation;radar target tracking;sensor tracking performance;similar sensors;state estimation;track fusion;Information filtering;Information filters;Multisensor systems;Noise measurement;Sensor fusion;Sensor phenomena and characterization;Sensor systems;State estimation;State feedback;Target tracking},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=984817&isnumber=21220

Tang Xiaoming, He You, Guan Jian and Jiang Benqing, "Hypotheses testing data fusion in a passive cross location system," Radar, 2001 CIE International Conference on, Proceedings, Beijing, 2001, pp. 748-752.
doi: 10.1109/ICR.2001.984823
Abstract: Eliminating the false intersection (deghosting) is a difficult problem in a passive cross location system. Using a decentralized decision fusion topology, a new deghosting algorithm derived from hypotheses test theory is developed, which is based on the geometrical position difference between ghosts and true targets relative to the deghosting sensor. Simulation results show the feasibility of the algorithm
keywords: {navigation;sensor fusion;decentralized decision fusion topology;deghosting algorithm;deghosting sensor;geometrical position difference;ghosts;hypotheses testing data fusion;multisensor distributed data fusion;passive cross location system;simulation results;time complexity reduction;true targets;Aerospace engineering;Azimuth;Circuit topology;Coordinate measuring machines;Helium;Noise measurement;Position measurement;Sensor fusion;System testing;Weapons},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=984823&isnumber=21220

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