Thursday, November 5, 2015

NRL picks U of Kansas for Work on SAR Signal Processing sole source

Work on SAR Signal Processing - Federal Business Opportunities: Opportunities

Title: Work on SAR Signal Processing

Sol. #: N00173-16-Q-0038

Agency: Department of the Navy
Office: Office of Naval Research
Location: Naval Research Laboratory/Supply

Posted On: Nov 04, 2015 2:29 pm

Base Type: Special Notice

Link: https://www.fbo.gov/spg/DON/ONR/3400/N00173-16-Q-0038/listing.html

The Naval Research Laboratory (NRL) intends to award a Sole Source contract to University of Kansas to furnish: Work on SAR Signal Processing - NRL Radar Division requires support with
development of several signal processing areas of research including 
  • multi-channel adaptive processing, 
  • waveform diversity, 
  • spectrally efficient waveform optimization, 
  • re-iterative minimum mean squared error (RMMSE) algorithm development, and 
  • multistatic adaptive processing. 
Services required will include advanced concept development for single and multi-channel synthetic aperture radar (SAR) systems and in-depth investigation of adaptive signal processing and waveform development to support concept. Modeling and simulation will be used to demonstrate performance of techniques and findings will be documented via publication in relevant conferences and journals. - PI has numerous publications and several essential patents that are fundamental to the program.

Related/Background:


References:

Blunt, S.D.; McCormick, P.; Higgins, T.; Rangaswamy, M., "Physical emission of spatially-modulated radar," in Radar, Sonar & Navigation, IET , vol.8, no.9, pp.1234-1246, 12 2014
doi: 10.1049/iet-rsn.2014.0057
Abstract: Leveraging the recent development of a physical implementation of arbitrary polyphase codes as spectrally well-contained waveforms, the notion of spatial modulation is developed whereby a time-varying beampattern is incorporated into the physical emission of an individual pulse. This subset of the broad category of MIMO radar is inspired by the operation of fixational eye movement within the human eye to enhance visual acuity and also subsumes the notion of the frequency-diverse array for application to pulsed radar. From this spatial modulation framework, some specific emission examples are evaluated in terms of resolution and sidelobe levels for the delay and angle domains. The impact of spatial modulation upon spectral content is also considered and possible joint delay-angle emission design criteria are suggested. Simulation results of selected target arrangements demonstrate the promise of enhanced discrimination and the basis for the development of future cognitive radar capabilities that may mimic salient aspects of the visual cortex.
keywords: {MIMO radar;modulation;phase coding;MIMO radar;angle domains;arbitrary polyphase codes;cognitive radar;delay domains;fixational eye movement;frequency-diverse array;human eye;joint delay-angle emission design criteria;physical emission;pulsed radar;sidelobe levels;spatial modulation framework;spatially-modulated radar;spectral content;spectrally well-contained waveforms;time-varying beampattern;visual acuity enhancement},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6985781&isnumber=6985776

Blunt, S.D.; Metcalf, J.G.; Biggs, C.R.; Perrins, E., "Performance Characteristics and Metrics for Intra-Pulse Radar-Embedded Communication," in Selected Areas in Communications, IEEE Journal on , vol.29, no.10, pp.2057-2066, December 2011
doi: 10.1109/JSAC.2011.111215
Abstract: Low probability of intercept (LPI) communication generally relies on the presence of noise to obfuscate a covert signal through the use of spectral spreading or hopping. In contrast, this paper addresses the use of ambient interference from other man-made emissions as a means to mask the presence of covert communication. Specifically, the high power, wide bandwidth, and repeating structure of pulsed radar systems provide an advantageous framework within which to embed a communication signal. The operating paradigm considered here is that of an RF tag/transponder that is illuminated by the radar and intends to covertly communicate with the radar or some other desired receiver while being masked by the ambient radar backscatter to avoid detection by an intercept receiver. Communication takes place on an intra-pulse (or individual pulse) basis to maximize the data rate. The impact of multipath, and its exploitation using time reversal to achieve spatio-temporal focusing, is considered. The processing gain for the destination receiver and intercept receiver are derived analytically and subsequently used to optimize the parameterization of communication symbol design.
keywords: {backscatter;radar;RF tag/transponder;communication signal;communication symbol design;covert communication;covert signal;intra-pulse radar-embedded communication;performance characteristics;pulsed radar systems;radar backscatter;spectral hopping;spectral spreading;Lighting;Military communication;Noise measurement;Radar scattering;Receivers;RFID tags;detectors;interference cancellation;military communication;radar clutter;spread spectrum communication;transponders},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6081358&isnumber=6081341

Blunt, S.D.; Higgins, T., "Dimensionality Reduction Techniques for Efficient Adaptive Pulse Compression," in Aerospace and Electronic Systems, IEEE Transactions on , vol.46, no.1, pp.349-362, Jan. 2010
doi: 10.1109/TAES.2010.5417167
Abstract: Adaptive filtering for radar pulse compression has been shown to improve sidelobe suppression through the estimation of an appropriate pulse compression filter for each individual range cell of interest. However, the relatively high computational cost of full-dimension, adaptive range processing may limit practical implementation in many current real-time systems. Dimensionality reduction techniques are here employed to approximate the framework for pulse compression filter estimation. Within this approximate framework, two new minimum mean square error (MMSE) based adaptive algorithms are derived. The two algorithms are denoted as specific embodiments of the fast adaptive pulse compression (FAPC) method and are shown to maintain performance close to that of full-dimension adaptive processing, while reducing computation cost by nearly an order of magnitude (in terms of the discretized waveform length N).
keywords: {adaptive filters;mean square error methods;pulse compression;radar signal processing;adaptive filtering;adaptive pulse compression;dimensionality reduction techniques;fast adaptive pulse compression method;minimum mean square error;radar pulse compression;sidelobe suppression;Adaptive filters;Computational efficiency;Filtering;Matched filters;Pulse compression methods;Pulse modulation;Radar cross section;Radar scattering;Real time systems;Signal to noise ratio},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5417167&isnumber=5417139

Blunt, S.D.; Yatham, P.; Stiles, J., "Intrapulse Radar-Embedded Communications," in Aerospace and Electronic Systems, IEEE Transactions on , vol.46, no.3, pp.1185-1200, July 2010
doi: 10.1109/TAES.2010.5545182
Abstract: The embedding of a covert communication signal amongst the ambient scattering from an incident radar pulse has previously been achieved by modulating a Doppler-like phase shift sequence over numerous pulses (i.e., on an inter-pulse basis). In contrast, this paper considers radar-embedded communications on an intrapulse basis whereby an incident radar waveform is converted into one of K communication waveforms, each of which acts as a communication symbol representing some predetermined information (e.g., a bit sequence). To preserve a low intercept probability, this manner of radar-embedded communications necessitates prudent selection of the set of communication waveforms as well as interference cancellation on receive. A general mathematical model and subsequent optimization problem is established for the design of the communication waveforms, from which three design strategies are developed. Also, receiver design issues are discussed, and an interference-canceling maximum likelihood receiver is presented. Performance results are presented in terms of the communication symbol error rate as well as a correlation-based metric from which intercept probability can be inferred. It is demonstrated that, given persistent radar illumination with a pulse repetition frequency (PRF) of 1–2 kHz, intrapulse radar-embedded communications can theoretically achieve data-rates commensurate with speech coding (for the interval of the radar dwell time) with the potential for even higher data-rates if additional diversity is appropriately incorporated.
keywords: {Design optimization;Error analysis;Frequency diversity;Interference cancellation;Lighting;Mathematical model;Phase modulation;Pulse modulation;Radar scattering;Radar theory},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5545182&isnumber=5545162

Blunt, S.D.; Shackelford, A.K.; Gerlach, K.; Smith, K.J., "Doppler Compensation & Single Pulse Imaging using Adaptive Pulse Compression," in Aerospace and Electronic Systems, IEEE Transactions on , vol.45, no.2, pp.647-659, April 2009
doi: 10.1109/TAES.2009.5089547
Abstract: The effects of target Doppler are addressed in relation to adaptive receive processing for radar pulse compression. To correct for Doppler-induced filter mismatch over a single pulse, the Doppler-compensated adaptive pulse compression (DC-APC) algorithm is presented whereby the respective Doppler shifts for large target returns are jointly estimated with the illuminated range profile and subsequently incorporated into the original APC adaptive receive filter formulation. As a result, the Doppler-mismatch-induced range sidelobes can be suppressed thereby regaining a significant portion of the sensitivity improvement that is possible when applying adaptive pulse compression (APC) without the existence of significant Doppler mismatch. In contrast, instead of compensating for Doppler mismatch, the single pulse imaging (SPI) algorithm generalizes the APC formulation for a bank of Doppler-shifted matched filters thereby producing a sidelobe-suppressed range-Doppler image from the return signal of a single radar pulse which is applicable for targets with substantial variation in Doppler. Both techniques are based on the recently proposed APC algorithm and its generalization, the multistatic adaptive pulse compression (MAPC) algorithm, which have been shown to be effective for the suppression of pulse compression range sidelobes thus dramatically increasing the sensitivity of pulse compression radar.
keywords: {Doppler radar;pulse compression;radar imaging;Doppler compensation;Doppler induced filter mismatch;adaptive pulse compression;adaptive receive processing;radar pulse compression;respective Doppler shifts;single pulse imaging;target Doppler;Adaptive filters;Doppler radar;Doppler shift;Matched filters;Phase detection;Pulse compression methods;Pulse modulation;Radar detection;Radar imaging;Radar scattering},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5089547&isnumber=5089526

Shackelford, A.K.; Gerlach, K.; Blunt, S.D., "Partially Adaptive STAP using the FRACTA Algorithm," in Aerospace and Electronic Systems, IEEE Transactions on , vol.45, no.1, pp.58-69, Jan. 2009
doi: 10.1109/TAES.2009.4805263
Abstract: A partially adaptive space-time adaptive processor (STAP) utilizing the recently developed FRACTA algorithm is presented which significantly reduces the high computational complexity and large sample support requirements of fully adaptive STAP. Multi-window post-Doppler dimensionality reduction techniques are employed to transform the data prior to application of the FRACTA algorithm. The FRACTA algorithm is a reiterative censoring (RC) and detection algorithm which has been shown to provide excellent detection performance in nonhomogeneous interference environments. Two multi-window post-Doppler dimensionality reduction techniques are considered: PRI-staggered and adjacent-bin. The partially adaptive FRACTA algorithm is applied to the KASSPER I (knowledge-aided sensor signal processing & expert reasoning) challenge datacube. The pulse repetition interval (PRI)-staggered approach with D=6 filters per Doppler bin is found to provide the best detection performance, outperforming the fully adaptive case while simultaneously reducing the runtime by a factor of ten. Using this implementation, partially adaptive FRACTA detects 197 out of 268 targets with one false alarm. The clairvoyant processor (the covariance matrix for each range cell is known) detects 198 targets with one false alarm. In addition, the partially adaptive FRACTA algorithm is shown to be resilient to jamming, and performs well for reduced sample support situations. When compared with partially adaptive STAP using traditional sliding window processing (SWP), the runtime of partially adaptive FRACTA is 14 times faster, and the detection performance is significantly increased (SWP detects 46 out of 268 targets with one false alarm).
keywords: {covariance matrices;inference mechanisms;radar signal processing;space-time adaptive processing;FRACTA algorithm;adaptive space-time adaptive processor;computational complexity;covariance matrix;datacube;detection algorithm;expert reasoning;knowledge-aided sensor signal processing;multiwindow post-Doppler dimensionality reduction techniques;nonhomogeneous interference environments;partially adaptive STAP;pulse repetition interval;reiterative censoring;sliding window processing;Clutter;Covariance matrix;Interference suppression;Jamming;Laboratories;Maximum likelihood detection;Maximum likelihood estimation;Runtime;Signal processing algorithms;Training data},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=4805263&isnumber=4805254

Blunt, S.D.; Gerlach, K.; Heyer, J., "HRR Detector for Slow-Moving Targets in Sea Clutter," in Aerospace and Electronic Systems, IEEE Transactions on , vol.43, no.3, pp.965-974, July 2007
doi: 10.1109/TAES.2007.4383586
Abstract: The radar detection of targets in the presence of sea clutter has historically relied upon the radial velocity of targets with respect to the radar platform either by exploiting the relative target Dopplers (for targets with sufficient radial velocity) or by discerning the paths targets traverse from scan to scan. For targets with little to no radial velocity component, though, it can become quite difficult to differentiate targets from the surrounding sea clutter. This paper addresses the detection of slow-moving targets in sea clutter using a high resolution radar (HRR) such that the target has perceptible extent in range. Under the assumption of completely random sea clutter spikes based on an epsiv-contaminated mixture model with the signal and clutter powers known, optimal detection performance results from using the likelihood ratio test (LRT). However, for realistic sea clutter, the clutter spikes tend to be a localized phenomenon. Based upon observations from real radar data measurements, a heuristic approach exploiting a salient aspect of the idealized LRT is developed which is shown to perform well when applied to real measured sea clutter.
keywords: {radar clutter;radar detection;radar resolution;target tracking;HRR detector;clutter spikes;high resolution radar;likelihood ratio test;optimal detection performance;radar detection;radar platform;radial velocity;relative target Dopplers;sea clutter;slow moving target detection;Bandwidth;Detectors;Light rail systems;Radar clutter;Radar detection;Radar imaging;Radar scattering;Radar tracking;Signal resolution;Synthetic aperture radar},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=4383586&isnumber=4383573

Gerlach, K.; Shackelford, A.K.; Blunt, S.D., "Combined Multistatic Adaptive Pulse Compression and Adaptive Beamforming for Shared-Spectrum Radar," in Selected Topics in Signal Processing, IEEE Journal of , vol.1, no.1, pp.137-146, June 2007
doi: 10.1109/JSTSP.2007.897041
Abstract: The recently proposed Multistatic Adaptive Pulse Compression (MAPC) algorithm has been shown to successfully suppress both range sidelobes and interference from multiple radars operating in the same spectrum, thus enabling shared-spectrum multistatic radar. In this paper, we present a method to increase the overall information capacity of the MAPC algorithm by performing joint adaptive pulse compression in conjunction with adaptive beamforming. The addition of an adaptive beamforming stage to the MAPC algorithm enables further mutual interference suppression and thus better estimation performance such that the number of multistatic radars simultaneously operating in the same spectrum may be increased for the same mean-square estimation error. Analysis of the performance of the adaptive beamforming MAPC algorithm in a variety of scenarios is presented. In addition, Monte Carlo analyses on the number of shared-spectrum radars are also presented
keywords: {Monte Carlo methods;array signal processing;interference suppression;mean square error methods;pulse compression;radar interference;radar signal processing;Monte Carlo analyses;adaptive beamforming;combined multistatic adaptive pulse compression;interference suppression;mean-square estimation error;multistatic radars;shared-spectrum radar;sidelobes suppression;Array signal processing;Communication industry;Interference suppression;Matched filters;Pulse compression methods;Radar applications;Radar scattering;Radar signal processing;Radio frequency;Signal processing algorithms;Adaptive processing;CLEAN;MIMO;adaptive matched filter;multistatic radar;pulse compression;radar;shared-spectrum radar;sidelobe cancellation;waveform diversity},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=4200700&isnumber=4200691

Blunt, S.D.; Gerlach, K., "Adaptive pulse compression via MMSE estimation," in Aerospace and Electronic Systems, IEEE Transactions on , vol.42, no.2, pp.572-584, April 2006
doi: 10.1109/TAES.2006.1642573
Abstract: Radar pulse compression involves the extraction of an estimate of the range profile illuminated by a radar in the presence of noise. A problem inherent to pulse compression is the masking of small targets by large nearby targets due to the range sidelobes that result from standard matched filtering. This paper presents a new approach based upon a minimum mean-square error (MMSE) formulation in which the pulse compression filter for each individual range cell is adaptively estimated from the received signal in order to mitigate the masking interference resulting from matched filtering in the vicinity of large targets. The proposed method is compared with the standard matched filter and least-squares (LS) estimation and is shown to be superior over a variety of stressing scenarios.
keywords: {least squares approximations;matched filters;mean square error methods;pulse compression;radar signal processing;radar theory;MMSE estimation;adaptive pulse compression;least squares estimation;masking interference;minimum mean square error;pulse compression filter;radar pulse compression;range profile;standard matched filtering;Adaptive filters;Autocorrelation;Filtering;Gaussian noise;Matched filters;Phase modulation;Pulse compression methods;Pulse modulation;Radar scattering;Signal to noise ratio},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=1642573&isnumber=34423

Blunt, S.D.; Gerlach, K.; Rangaswamy, M., "Stap using knowledge-aided covariance estimation and the fracta algorithm," in Aerospace and Electronic Systems, IEEE Transactions on , vol.42, no.3, pp.1043-1057, July 2006
doi: 10.1109/TAES.2006.248197
Abstract: In the airborne space-time adaptive processing (STAP) setting, a priori information via knowledge-aided covariance estimation (KACE) is employed in order to reduce the required sample support for application to heterogeneous clutter scenarios. The enhanced FRACTA (FRACTA.E) algorithm with KACE as well as Doppler-sensitive adaptive coherence estimation (DS-ACE) is applied to the KASSPER I & II data sets where it is shown via simulation that near-clairvoyant detection performance is maintained with as little as 1/3 of the normally required number of training data samples. The KASSPER I & II data sets are simulated high-fidelity heterogeneous clutter scenarios which possess several groups of dense targets. KACE provides a priori information about the clutter covariance matrix by exploiting approximately known operating parameters about the radar platform such as pulse repetition frequency (PRF), crab angle, and platform velocity. In addition, the DS-ACE detector is presented which provides greater robustness for low sample support by mitigating false alarms from undernulled clutter near the clutter ridge while maintaining sufficient sensitivity away from the clutter ridge to enable effective target detection performance
keywords: {covariance analysis;expert systems;knowledge based systems;radar signal processing;space-time adaptive processing;Doppler-sensitive adaptive coherence estimation;KASSPER;airborne space-time adaptive processing;clutter ridge;enhanced FRACTA algorithm;knowledge-aided covariance estimation;target detection;Airborne radar;Covariance matrix;Detectors;Interference;Laboratories;Radar clutter;Radar detection;Signal processing algorithms;Spaceborne radar;Training data},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=4014430&isnumber=4014422

Blunt, S.D.; Gerlach, K., "Multistatic adaptive pulse compression," in Aerospace and Electronic Systems, IEEE Transactions on , vol.42, no.3, pp.891-903, July 2006
doi: 10.1109/TAES.2006.248196
Abstract: A new technique denoted as multistatic adaptive pulse compression (MAPC) is introduced which exploits recent work on adaptive pulse compression (APC) in order to jointly separate and pulse compress the concurrently received return signals from K proximate multistatic radars operating (i.e., transmitting) within the same spectrum. For the return signal from a single pulse of a monostatic radar, APC estimates the particular receive filter for a given range cell in a Bayesian sense reiteratively by employing the matched filter estimates of the surrounding range cell values as a priori knowledge in order to place temporal (i.e., range) nulls at the relative ranges occupied by large targets and thereby suppress range sidelobes to the level of the noise. The MAPC approach generalizes the APC concept by jointly estimating the particular receive filter for each range cell associated with each of several concurrently-received radar return signals occupying the same spectrum. As such, MAPC is found to enable shared-spectrum multistatic operation and is shown to yield substantial performance improvement in the presence of multiple spectrum-sharing radars as compared with both standard matched filters and standard least-squares mismatched filters
keywords: {adaptive filters;adaptive radar;pulse compression;radar signal processing;Bayesian sense;K proximate multistatic radars;least squares mismatched filters;matched filters;monostatic radar;multistatic adaptive pulse compression;receive filter;Bandwidth;Bayesian methods;Frequency diversity;Matched filters;Noise level;Pulse compression methods;Pulse modulation;Radar applications;Radar imaging;Radar signal processing},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=4014429&isnumber=4014422

Blunt, S.D.; Gerlach, K., "Efficient robust AMF using the FRACTA algorithm," in Aerospace and Electronic Systems, IEEE Transactions on , vol.41, no.2, pp.537-548, April 2005
doi: 10.1109/TAES.2005.1468746
Abstract: The FRACTA algorithm has been shown to be an effective space-time adaptive processing (STAP) methodology for the airborne radar configuration in which there exists nonhomogeneous clutter, jamming, and dense target clusters. Further developments of the FRACTA algorithm are presented here in which the focus is on the robust, efficient implementation of the FRACTA algorithm. Enhancements to the FRACTA algorithm include a censoring stopping mechanism, an alternative data blocking approach for adaptive power residue (APR) censoring, and a fast reiterative censoring (RC) procedure. Furthermore, a coherent processing interval (CPI) segmentation scheme for computing the adaptive weights is presented as an alternative approach to computing the adaptive matched filter (AMF) weight vector that allows for lower sample support and reduced computational complexity. The enhanced FRACTA algorithm, denoted as FRACTA.E, is applied to the KASSPER I challenge datacube which possesses dense ground target clusters that are known to have a significant deleterious effect on standard adaptive matched filtering (AMF) processors. It is shown that the FRACTA.E algorithm outperforms and is considerably more computationally efficient than both the original FRACTA algorithm and the standard sliding window processing (SWP) approach. Furthermore, using the KASSPER I datacube, the FRACTA.E algorithm is shown to have the same detection performance as the clairvoyant algorithm where the exact range-dependent clutter covariance matrices are known.
keywords: {adaptive filters;airborne radar;covariance matrices;jamming;matched filters;radar clutter;radar detection;radar receivers;radar signal processing;radar tracking;space-time adaptive processing;target tracking;FRACTA algorithm;FRACTA.E algorithm;KASSPER I datacube;adaptive matched filter weight vector;adaptive matched filtering;adaptive power residue censoring;adaptive weights;airborne radar configuration;censoring stopping mechanism;clutter covariance matrices;coherent processing interval;computational complexity;data blocking approach;ground target clusters;jamming;reiterative censoring procedure;segmentation scheme;sliding window processing;space-time adaptive processing;Adaptive filters;Airborne radar;Clustering algorithms;Clutter;Computational complexity;Covariance matrix;Filtering algorithms;Jamming;Matched filters;Robustness},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=1468746&isnumber=31509

Gerlach, K.; Blunt, S.D.; Picciolo, M.L., "Robust adaptive matched filtering using the FRACTA algorithm," in Aerospace and Electronic Systems, IEEE Transactions on , vol.40, no.3, pp.929-945, July 2004
doi: 10.1109/TAES.2004.1337465
Abstract: An effective method is developed for selecting sample snapshots for the training data used to compute the adaptive weights for an adaptive match filter (AMF); specifically a space/time adaptive processing (STAP) airborne radar configuration is considered. In addition, a new systematic robust adaptive algorithm is presented and evaluated against interference scenarios consisting of jamming, nonhomogeneous airborne clutter (generated by the Research Laboratory STAP (RLSTAP) or knowledge-aided sensor signal processing and expert reasoning (KASSPER) high-fidelity clutter models or using the multi-channel airborne radar measurement (MCARM) clutter data base), internal system noise, and outliers (which could take the form of targets themselves). The new algorithm arises from empirical studies of several combinations of performance metrics and processing configurations. For culling the training data, the generalized inner product (GIP) and adaptive power residue (APR) are examined. In addition two types of data processing methods are considered and evaluated: sliding window processing (SWP) and concurrent block processing (CBP). For SWP, a distinct adaptive weight is calculated for each cell-under-test (CUT) in a contiguous set of range cells. For one configuration of CBP, two distinct weights are calculated for a contiguous set of CUTs. For the CBP, the CUTs are in the initial training data and there are no guard cells associated with the CUT as there would be for SWP. Initial studies indicate that the combination of using the fast maximum likelihood (FML) algorithm, reiterative censoring, the APR metric, CBP, the two-weight method, and the adaptive coherence estimation (ACE) metric (we call this the FRACTA algorithm) provides a basis for effective detection of targets in nonhomogeneous interference. For the KASSPER data, FRACTA detects 154 out of 268 targets with one false alarm (PF≈3×10-5) whereas the FML algorithm with SWP detects 11 with one false alarm. The clarvoyant processor (where each range cell's covariance matrix is known) detects 192 targets with one false alarm.
keywords: {adaptive filters;airborne radar;matched filters;maximum likelihood estimation;noise;radar clutter;radar signal processing;space-time adaptive processing;APR metric;FRACTA algorithm;Research Laboratory STAP;adaptive algorithm;adaptive coherence estimation metric;adaptive matched filtering;adaptive power residue;adaptive weights;airborne radar configuration;cell-under-test;clutter data base;concurrent block processing;data processing methods;expert reasoning;fast maximum likelihood algorithm;generalized inner product;interference scenarios;internal system noise;jamming;knowledge-aided sensor signal processing;multichannel airborne radar measurement;nonhomogeneous airborne clutter;nonhomogeneous interference;outliers;performance metrics;processing configurations;reiterative censoring;sliding window processing;space/time adaptive processing;two-weight method;Adaptive filters;Airborne radar;Clutter;Filtering algorithms;Interference;Matched filters;Maximum likelihood detection;Robustness;Signal processing algorithms;Training data},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=1337465&isnumber=29502


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