Micro-Doppler Detection and Classification of Radar Targets with moving parts

. The range-Doppler images of the simulated human gait

Micro-Doppler Characteristics of Radar Targets - 1st Edition

Authors: Qun Zhangm, Ying Luo, Yong-an Chen

Paperback ISBN: 9780128098615

eBook ISBN: 9780128098837

Imprint: Butterworth-Heinemann

Published Date: 1st November 2016

Page Count: 224

UC San Diego / Micro-Doppler Characteristics of Radar Targets

by Qun Zhang (Author), Ying Luo (Author), Yong-an Chen (Author) 

Micro-Doppler Characteristics of Radar Targets is a monograph on radar target’s micro-Doppler effect theory and micro-Doppler feature extraction techniques. The micro-Doppler effect is presented from two aspects, including micro-Doppler effect analysis and micro-Doppler feature extraction, with micro-Doppler effects induced by different micro-motional targets in different radar systems analyzed and several methods of micro-Doppler feature extraction and three-dimensional micro-motion feature reconstruction presented.

The main contents of this book include micro-Doppler effect in narrowband radar, micro-Doppler effect in wideband radar, micro-Doppler effect in bistatic radar, micro-Doppler feature analysis and extraction, and three-dimensional micro-motion feature reconstruction, etc.

This book can be used as a reference for scientific and technical personnel engaged in radar signal processing and automatic target recognition, etc. It is especially suitable for beginners who are interested in research on micro-Doppler effect in radar.

• Presents new views on micro-Doppler effects, analyzing and discussing micro-Doppler effect
  in wideband radar rather than focusing on narrowband Provides several new methods for micro-Doppler feature extraction which are very helpful and practical for readers
• Includes practical cases that align with main MATLAB codes in each chapter, with detailed program annotations

Related/Background:

IET Digital Library: Radar Micro-Doppler Signatures: Processing and Applications

Editors: Victor C. Chen;  David Tahmoush; William J. Miceli View affiliations

Publication Year: 2014

The micro-Doppler effect appears as Doppler frequency modulations in coherent laser or microwave radar systems induced by mechanical vibrations or rotations of a target or any part on the target. These Doppler modulations become a distinctive signature of a target that incorporates vibrating or rotating structures, and provides evidence of the identity of the target with movement. This book concentrates on the processing and application of radar micro-Doppler signatures in real world situations, providing readers with a working knowledge on various applications of radar micro-Doppler signatures such as detection, tracking and discrimination of vehicles and dismounts,  identifying human movement based on radar micro-Doppler signatures, detection and tracking small boats in sea, detection and discrimination complex motion of missile warheads, discrimination of quadrupedal animals, and detection and tracking of flying birds. Topics covered include bistatic/multistatic micro-Doppler signatures, decomposition of micro-Doppler signatures, through-wall radar micro-Doppler signatures and ultrasound micro-Doppler signature studies. Radar Micro-Doppler Signatures: Processing and applications will be of interest to R&D researchers and engineers in government research centers, industries, and universities around the world who work
on radar imaging and signal analysis, target feature extraction, and non-cooperative target  recognition.


M. K. McDonald, "Discrimination of human targets for radar surveillance via micro-Doppler characteristics," in IET Radar, Sonar & Navigation, vol. 9, no. 9, pp. 1171-1180, 12 2015.
doi: 10.1049/iet-rsn.2015.0049
Abstract:
An approach is examined for reducing false alarms during detection of
human targets via radar surveillance from moving platforms. The ability
to distinguish between human target and clutter discrete micro-Doppler
signatures is quantified using simulated and real data collected using
the DORC X-band wideband experimental airborne radar. Signal processing
methodologies to extract key target signature characteristics are
discussed along with separability of target classes and classifier
performance.
keywords: {Doppler radar;airborne radar;object
detection;radar signal processing;signal detection;DORC X-band wideband
experimental airborne radar;classifier performance;clutter discrete
microDoppler signatures;false alarm reduction;human target
detection;human target discrimination;key target signature
characteristics extraction;microDoppler characteristics;moving
platforms;radar surveillance;signal processing methodologies;target
classes},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7348898&isnumber=7348873

J.
Wang, P. Lei, J. Sun and W. Hong, "Spectral characteristics of mixed
micro-doppler timefrequency data sequences in micro-motion and inertial
parameter estimation of radar targets," in IET Radar, Sonar & Navigation, vol. 8, no. 4, pp. 275-281, April 2014.
doi: 10.1049/iet-rsn.2013.0108
Abstract:
Time variation of micro-Doppler (mD) frequency is an important
representation of target's micro-motions and intrinsic attributes in
radar signals. For free rigid targets consisting of multiple scatterers,
mixed mD time-frequency (TF) data sequences based on two-dimensional TF
distributions of mD signals demonstrates effectiveness and simplicity
to estimate targets' micromotion and inertial parameters. In this study
the authors further explore the feasibility of the estimation method by
studying the spectral characteristics of the mixed sequence. The
construction of mixed mD TF data sequence is introduced, and then the
analysis of its spectrum is conducted with the help of mathematical
derivation and simulations. It is found that one of observation angles
plays a leading role in relative amplitudes of spectral components, and
could accordingly determine the optimal radar observation region for
given micro-dynamic targets. It could contribute to the proper placement
of radar station, and help identify some desired spectral components
accurately in the blind condition for the purpose of parameter
estimation of micro-dynamic targets.
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6825700&isnumber=6783560

X.
Chen, Xiaohan Yu, J. Guan and Jian Zhang, "Detection and extraction of
marine target with micromotion via short-time fractional Fourier
transform in sparse domain," 2016 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC), Hong Kong, 2016, pp. 1-5.
doi: 10.1109/ICSPCC.2016.7753734
Abstract:
The micro-Doppler (m-D) signatures can describe the refined motion
characteristics of a marine target, which are helpful for target
detection and recognition. Due to the complex sea clutter and m-D of
marine target, traditional detection methods using time-frequency
analysis have great limitations on accuracy and computational cost. In
this paper, the micromotion signal model of sea surface target is
firstly established according to the length of observation time. Then a
novel detection and m-D extraction method is established via sparse
time-frequency analysis, i.e., short-time fractional Fourier transform
in sparse domain (SSTFRFT). The definition and calculation are described
in detail. Finally, experimental results using real radar data, i.e.,
S-band searching radar (SSR) data, indicate that the proposed method can
achieve excellent detection performance and lower computational cost
with higher accuracy compared with the traditional methods.

keywords: {fast Fourier transforms;object detection;object
recognition;radar detection;S-band searching radar;m-D extraction
method;marine target detection;marine target extraction;microDoppler
signatures;micromotion fractional Fourier transform;refined motion
characteristics;short-time fractional Fourier transform;sparse
domain;target recognition;time-frequency analysis;Clutter;Marine
vehicles;Radon;Ribs;Sea surface;Sensors;Surface waves;Marine target
detection;Micro-Doppler (m-D);Sea clutter;Short-time fractional Fourier
transform (STFRFT);Sparse time-frequency analysis},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7753734&isnumber=7753583

X. Chen, J. Guan, Z. Zhao and H. Ding, "Micro-Doppler signatures of sea surface targets and applications to radar detection," 2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Beijing, 2016, pp. 2726-2729.
doi: 10.1109/IGARSS.2016.7729704
Abstract:
The micro-motion of a subject induces Doppler frequency modulations
around the carrier frequency of the reflected sensor signals. Recently,
it has been proved that sea clutter is significantly variable and sea
surface subjects have their micro-motions influenced by the sea state.
The micro-Doppler (m-D) signatures can describe the refined motion
characteristics of sea surface target. The micromotion signal model of
sea surface target is established in this paper based on the length of
observation time. Finally, the micromotion properties are analyzed using
real radar data, i.e., X-band Council for Scientific and Industrial
Research (CSIR) data and S-band radar data. It also proves that the m-D
can provide extra information of target, which would help improve radar
detection and recognition abilities.
keywords: {Doppler radar;radar
detection;CSIR data;Doppler frequency modulations;S-band radar
data;X-band Council for Scientific and Industrial Research data;carrier
frequency;m-D signatures;micro-Doppler
signatures;micromotions;observation time;radar detection;radar
recognition abilities;real radar data;reflected sensor signals;sea
clutter;sea surface targets;Clutter;Doppler effect;Doppler
radar;Frequency modulation;Radar detection;Sea
surface;Micro-Doppler;Radar detection;Sea clutter;Sea surface target},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7729704&isnumber=7728980

O.
Karabayır, S. M. Yücedağ, O. M. Yücedağ, A. F. Coşkun and H. A. Serim,
"Micro-Doppler-based classification study on the detections of aerial
targets and wind turbines," 2016 17th International Radar Symposium (IRS), Krakow, 2016, pp. 1-4.
doi: 10.1109/IRS.2016.7497361
Abstract:
In this study, micro-Doppler-based aerial target classification is
examined together with the consideration of wind turbine clutter (WTC).
In the examinations, wavelet coefficients extracted from micro-Doppler
profiles are employed as classifier features for the airliner-, glider-
and helicopter-type aerial targets and also for the examined wind
turbine (WT) model. In order to simulate the targets' scatterings more
accurately, their computer-aided design (CAD) models are considered.
Moreover, scattering characteristics of the targets are taken into
account for a variety of radar aspects and propeller or blade rotation
speeds. Through the simulation results obtained by employing Bayesian
and probabilistic neural network (PNN) classifiers, classification
performance of a typical air traffic control (ATC) radar system is
exhibited. Additionally, the results present the recognisability of WTC
on ATC systems via the classification procedure.
keywords:
{CAD;Doppler radar;aerospace computing;air traffic control;airborne
radar;belief networks;helicopters;neural nets;pattern
classification;propellers;radar clutter;wind turbines;ATC radar
system;Bayesian neural network classifier;CAD model;PNN
classifier;WTC;aerial target detection;air traffic control radar
system;airliner-type aerial target;blade rotation speed;computer-aided
design model;glider-type aerial target;helicopter-type aerial
target;microDoppler-based aerial target classification;probabilistic
neural network classifier;propeller;wavelet coefficient;wind
turbine;wind turbine clutter;Atmospheric modeling;Doppler radar;Feature
extraction;Helicopters;Solid modeling;Wind turbines;Aerial Target
Classification;Micro-Doppler Features;Wind Turbine Clutter},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7497361&isnumber=7497259

P.
Xia, X. R. Wan, J. X. Yi and H. Tang, "Micro-Doppler imaging for fast
rotating targets using illuminators of opportunity," in IET Radar, Sonar & Navigation, vol. 10, no. 6, pp. 1024-1029, 7 2016.
doi: 10.1049/iet-rsn.2015.0206
Abstract:
In recent years the use of illuminators of opportunity for target
detection and tracking has received renewed interest. Most aerial
targets have some forms of fast rotating structures that cause
micro-Doppler (m–D) effect and can be used to assist in the classification process. There is also a good potential to use m–D
for imaging such rotating structure because they contain geometry
characteristic information about the rotating structure. The imaging
results are expected to provide richer information for classification
purposes. Conventional inverse synthetic aperture radar requires small
rotation angle as well as wideband waveform. Tomography provides an
opportunity to image fast rotating targets for narrowband continuous
wave radar using m–D information only. This study first introduces the foundations of m–D
imaging. Then, the simulation results are presented. Finally, the field
experiments are described, together with the illustration and analysis
of typical experimental results. Both the simulations and experimental
data validate the effectiveness of the method.
keywords: {CW
radar;object detection;synthetic aperture radar;target tracking;fast
rotating targets;geometry characteristic information;inverse synthetic
aperture radar;m-D imaging;micro-Doppler imaging;narrowband continuous
wave radar;target detection;target tracking},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7491491&isnumber=7491490

O. A. Krasnov and A. G. Yarovoy, "Polarimetric micro-Doppler characterization of wind turbines," 2016 10th European Conference on Antennas and Propagation (EuCAP), Davos, 2016, pp. 1-5.
doi: 10.1109/EuCAP.2016.7481496
Abstract:
The article presents wind turbines polarimetric micro-Doppler radar
backscattering characteristics, which were measured by the PARSAX radar
using high resolution sounding signals with dual orthogonality. Such
signals provide the possibility to measure all elements of polarization
backscattering matrix of radar target simultaneously that especially
important for the analysis of moving targets polarimetric micro-Doppler
patterns. Such information can be used for better understanding of
electromagnetic wave scattering processes and development effective
algorithms for the mitigation of resulting dynamic clutter.

keywords: {Doppler radar;backscatter;electromagnetic wave
scattering;matrix algebra;radar polarimetry;wind turbines;PARSAX
radar;electromagnetic wave scattering processes;high resolution sounding
signals;polarization backscattering matrix;radar target;turbines
polarimetric microDoppler radar backscattering characteristics;wind
turbines;Doppler radar;Radar cross-sections;Radar polarimetry;Radar
scattering;Wind turbines;micro-Doppler;radar polarimetry;wind turbines},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7481496&isnumber=7481093

P.
Xia, X. R. Wan, J. X. Yi, Y. H. Rao and H. Y. Ke, "Investigations
toward micro-Doppler effect in digital broadcasting based passive
radar," IET International Radar Conference 2015, Hangzhou, 2015, pp. 1-5.
doi: 10.1049/cp.2015.1191
Abstract:
This paper proposes a passive bistatic radar (PBR) configuration using
digital broadcasting as an illuminator for micro-Doppler effect
experiments. First, the problems caused by a typical PBR usage scenario
are introduced and the corresponding signal processing techniques are
presented. Then, passive radar demonstrator and the experiments are
described. Last, typical experimental results are illustrated and
analyzed, which indicates the potential of PBR systems to detect
target's micro-Doppler signature and measure their characteristic
parameters.
keywords: {Doppler effect;passive radar;radar signal
processing;radio broadcasting;PBR configuration;PBR usage
scenario;digital broadcasting;microDoppler effect;microDoppler
signature;passive bistatic radar configuration;passive radar
demonstrator;signal processing;Digital Broadcasting;Micro-Doppler
Analysis;Multipath Clutter Rejection;Passive Radar;Reference Signal
Extraction},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7455413&isnumber=7441332

L. Xu, D. Feng and X. Wang, "Improved synthetic aperture radar micro-Doppler jamming method based on phase-switched screen," in IET Radar, Sonar & Navigation, vol. 10, no. 3, pp. 525-534, 3 2016.
doi: 10.1049/iet-rsn.2015.0266
Abstract:
Target micro-motions such as rotation and vibration introduce phase
modulation, termed as micro-Doppler (m-D) effect, onto synthetic
aperture radar (SAR) signals. This causes ghost targets in the
reconstructed SAR images. Inspired by this unique characteristic, a
passive-jamming method based on m-D was developed for SAR. The m-D
jamming method utilised a rotating reflector to intentionally generate
ghost targets as jamming strips on the SAR image so as to protect
certain areas. The m-D jamming method based on a single rotating
reflector can only generate a long jamming strip along the azimuth
direction but located in a finite number of range cells, which restricts
the region of protected scene. In this study, an improved m-D jamming
method based on phase-switched screen (PSS) is proposed, which combines
the advantage induced by the PSS modulation and the usefulness of the
m-D jamming. By controlling the modulating frequency and waveform of the
PSS, the jamming strip is enlarged along the range direction.
Theoretical analyses and simulation results verify the validity of the
proposed method.
keywords: {Doppler radar;jamming;radar
imaging;synthetic aperture radar;PSS modulation;SAR signals;azimuth
direction;passive jamming method;phase switched screen;phase-switched
screen;reconstructed SAR images;rotating reflector;single rotating
reflector;synthetic aperture radar micro-Doppler jamming method},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7410937&isnumber=7410925

R. M. Narayanan and M. Zenaldin, "Radar micro-Doppler signatures of various human activities," in IET Radar, Sonar & Navigation, vol. 9, no. 9, pp. 1205-1215, 12 2015.
doi: 10.1049/iet-rsn.2015.0173
Abstract:
This study presents the results of the authors' experimental
investigation into the radar micro-Doppler signatures (MDS) of various
human activities both in free-space and through-wall environments. The
collection of MDS signatures was divided into three categories:
stationary, forward-moving, and multi-target. Each category of MDS
signatures encompassed a variety of movements associated with it, adding
up to a total of 18 human movements. Using a 6.5-GHz C-band coherent
radar, the MDS of six human subjects were gathered in free-space and
through-wall environments. The MDS for these cases were analysed in
detail and the general properties of the signatures were related to
their associated phenomenological characteristics. Based upon the MDS,
features for designing detectors and classifiers of human targets
performing such movements are recommended. In the case of multiple human
targets in the radar field of view, it was found that it is possible to
distinguish these targets from the MDS under certain circumstances, but
not under others.
keywords: {Doppler radar;radar detection;C-band
coherent radar;MDS signatures;forward-moving category;frequency 6.5
GHz;multitarget category;phenomenological characteristics;radar
micro-Doppler signatures;stationary category;target classifiers;target
detection},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7348882&isnumber=7348873

X.
Chen, J. Guan, X. Li and Y. He, "Effective coherent integration method
for marine target with micromotion via phase differentiation and
radon-Lv's distribution," in IET Radar, Sonar & Navigation, vol. 9, no. 9, pp. 1284-1295, 12 2015.
doi: 10.1049/iet-rsn.2015.0100
Abstract:
Effective detection of marine targets with low observability gives a
severe challenge to radar signal processing. The micro-Doppler (m-D)
signatures of marine target can provide extra information for
non-stationary and time-varying signal analysis. Long-time integration
is an effective way to strengthen the m-D signal and improve
signal-to-clutter ratio. However, the performances are affected by the
range across unit and Doppler frequency migration effects. In this
study, m-D characteristics of marine target are studied and a novel
representation, i.e. phase differentiation and Radon-Lv's distribution
(PD-RLVD), is proposed to detect the m-D signal to realise the long-time
coherent integration. The PD-RLVD can accurately and directly represent
the m-D signal in the chirp rate and chirp change domain appearing as
obvious peaks. The proposed method is simple not only because it only
requires a 2D Fourier transform of the scaled Radon instantaneous
auto-correlation function after PD, but also for not introducing any
non-physical attributes. Relations between PD-RLVD and other integration
methods are introduced as well. Experiments with real data show that
the proposed method can achieve higher integration gain, detection
probability, and accuracies of motion parameter estimation.

keywords: {Radon transforms;correlation methods;integration;marine
radar;motion estimation;parameter estimation;radar clutter;radar
detection;radar signal processing;signal representation;statistical
distributions;2D Fourier transform;Doppler frequency migration
effects;PD-RLVD;Radon-Lv distribution;chirp change;chirp rate;detection
probability;effective coherent integration method;effective marine
target detection;integration gain;m-D signal representation;micro
Doppler signatures;micromotion;motion parameter estimation
accuracies;nonstationary signal analysis;phase differentiation;radar
signal processing;scaled Radon instantaneous autocorrelation
function;signal-to-clutter ratio improvement;time-varying signal
analysis},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7348899&isnumber=7348873

D.
Gaglione, C. Clemente, F. Coutts, Gang Li and J. J. Soraghan,
"Model-based sparse recovery method for automatic classification of
helicopters," 2015 IEEE Radar Conference (RadarCon), Arlington, VA, 2015, pp. 1161-1165.
doi: 10.1109/RADAR.2015.7131169
Abstract:
The rotation of rotor blades of a helicopter induces a Doppler
modulation around the main Doppler shift. Such a non-stationary
modulation, commonly called micro-Doppler signature, can be used to
perform classification of the target. In this paper a model-based
automatic helicopter classification algorithm is presented. A sparse
signal model for radar return from a helicopter is developed and by
means of the theory of sparse signal recovery, the characteristic
parameters of the target are extracted and used for the classification.
This approach does not require any learning process of a training set or
adaptive processing of the received signal. Moreover, it is robust with
respect to the initial position of the blades and the angle that the
LOS forms with the perpendicular to the plane on which the blades lie.
The proposed approach is tested on simulated and real data.

keywords: {Doppler shift;blades;helicopters;modulation;rotors
(mechanical);signal classification;Doppler modulation;Doppler shift;LOS
forms;adaptive processing;blades;learning process;microDoppler
signature;model-based automatic helicopter classification
algorithm;model-based sparse recovery method;nonstationary
modulation;rotor blades rotation;sparse signal
recovery;Blades;Dictionaries;Helicopters;Matching pursuit
algorithms;Radar imaging;Signal to noise ratio},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7131169&isnumber=7130933

Z.
r. Chen, H. Gu, W. m. Su and Z. Wang, "Micro-Doppler separation from
Time Frequency Distribution based on direction pattern," 2014 12th International Conference on Signal Processing (ICSP), Hangzhou, 2014, pp. 2116-2119.
doi: 10.1109/ICOSP.2014.7015368
Abstract:
Micro-Doppler (m-D) is a useful feature of radar target, as an
important characteristic for radar target detection, recognition, and
classification. However, since the form of m-D signals is always
multi-component, the signals usually need to be separated before feature
extraction. A method for separation the m-D signals is proposed based
on direction pattern. In this paper, we first obtain the Time Frequency
Distribution (TFD) of the target echo by Short-Time Fourier Transformer
(STFT). Then the local maxima algorithm is applied for the instantaneous
frequency (IF) track coherence. Finally, the direction patter algorithm
is used to separate the m-D signals. Simulation results indicate that
the proposed method is effective.
keywords: {Doppler radar;Fourier
transforms;feature extraction;frequency estimation;image
classification;object detection;object recognition;radar detection;radar
imaging;source separation;time-frequency analysis;IF track
coherence;STFT;TFD;direction patter algorithm;feature
extraction;instantaneous frequency track coherence;local maxima
algorithm;mD signal separation;microDoppler image separation;radar
target classification;radar target detection;radar target
recognition;short-time Fourier transformer;target echo;time-frequency
distribution;Doppler effect;Feature extraction;Filtering
algorithms;Indexes;Radar;Simulation;Time-frequency
analysis;Micro-Doppler;direction pattern;instantaneous frequency
estimation},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7015368&isnumber=7014954

R.
I. A. Harmanny, J. J. M. de Wit and G. P. Cabic, "Radar micro-Doppler
feature extraction using the spectrogram and the cepstrogram," 2014 11th European Radar Conference, Rome, 2014, pp. 165-168.
doi: 10.1109/EuRAD.2014.6991233
Abstract:
The radar micro-Doppler signature of a target is determined by parts of
the target moving or rotating in addition to the main body motion. The
relative motion of parts is characteristic for different classes of
targets, e.g. the flapping motion of a bird's wings vs. the spinning of
propeller blades. In the present study, the micro-Doppler signature is
exploited to discriminate birds and small unmanned aerial vehicles
(UAVs). Emphasis is on micro-Doppler features that can be extracted from
spectrograms and cepstrograms, enabling the human eye or indeed
automatic classification algorithms to make a quick distinction between
man-made objects and bio-life. In addition, in case of man-made objects,
it is desired to further characterize the type of mini-UAV to aid the
threat assessment. Also this characterization is done on the basis of
micro-Doppler features.
keywords: {Doppler radar;autonomous aerial
vehicles;feature extraction;radar detection;automatic classification
algorithms;cepstrograms;man-made objects;mini-UAV;propeller blades;radar
micro-Doppler feature extraction;spectrograms;unmanned aerial
vehicles;Birds;Blades;Feature extraction;Radar
cross-sections;Rotors;Spectrogram;birds;cepstrum;classification;mini-UAVs;radar;time-frequency
analysis},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6991233&isnumber=6986107

B. Erol, C. Karabacak, S. Z. Gürbüz and A. C. Gürbüz, "Simulation of human micro-Doppler signatures with Kinect sensor," 2014 IEEE Radar Conference, Cincinnati, OH, 2014, pp. 0863-0868.
doi: 10.1109/RADAR.2014.6875712
Abstract:
The availability and access to real radar data collected for targets
with a desired characteristic is often limited by monetary and practical
resources, especially in the case of airborne radar. In such cases, the
generation of accurate simulated radar data is critical to the
successful design and testing of radar signal processing algorithms. In
the case of human micro-Doppler research, simulations of the expected
target signature are required for a wide parameter space, including
height, weight, gender, range, angle and waveform. The applicability of
kinematic models is limited to just walking, while the use of motion
capture databases is restricted to the test subjects and scenarios
recorded by a third-party. To enable the simulation of human
micro-Doppler signatures at will, this work exploits the inexpensive
Kinect sensor to generate human spectrograms of any motion and for any
subject from skeleton tracking data. The simulated spectrograms
generated are statistically compared with those generated from high
quality motion capture data. It is shown that the Kinect spectrograms
are of sufficient quality to be used in simulation and classification of
human micro-Doppler.
keywords: {airborne radar;electric sensing
devices;radar signal processing;radar tracking;signal
classification;Kinect sensor;Kinect spectrogram;airborne radar;human
micro-Doppler signature classification;human spectrogram
generation;kinematic model;motion capture database;radar signal
processing algorithm;simulated radar data generation;skeleton tracking
data;Feature extraction;Joints;Legged locomotion;Radar
tracking;Spectrogram},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6875712&isnumber=6875503

Z. A. Cammenga, C. J. Baker, G. E. Smith and R. Ewing, "Micro-Doppler target scattering," 2014 IEEE Radar Conference, Cincinnati, OH, 2014, pp. 1451-1455.
doi: 10.1109/RADAR.2014.6875829
Abstract:
Micro-Doppler radar has proven to be a valuable tool in which
micro-motions are encoded into detailed target signatures that greatly
aid identification. Models of such targets often have elaborate motion
representations but only use a simple point scatterer representation to
compute received echo strength. Here, using simulations, we examine
micro-Doppler target signatures of simple combinations of point scatters
occupying a given resolution cell. Results show that more complex and
subtle behaviors occur than might be evident from a cursory analysis.
Further, we show, as the aspect angle of the target changes, so too does
the form of scattered signal. Together these two characteristics of
micro-Doppler signatures provide additional information about targets
and scenarios that could further aid identification.
keywords:
{Doppler radar;backscatter;micromechanical devices;radar signal
processing;signal representation;cursory analysis;microDoppler
radar;microDoppler target scattering;microDoppler target
signatures;motion representations;point scatterer
representation;resolution cell;Computational modeling;Doppler
effect;Doppler radar;Radar
cross-sections;Scattering;Spectrogram;micro-Doppler;phase;radar},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6875829&isnumber=6875503

Y. Luo, Q. Zhang, N. Yuan, F. Zhu and F. Gu, "Three-dimensional precession feature extraction of space targets," in IEEE Transactions on Aerospace and Electronic Systems, vol. 50, no. 2, pp. 1313-1329, April 2014.
doi: 10.1109/TAES.2014.110545
Abstract:
Precession is one of the most common kinds of micro-motions for space
targets. Because the precession of a target consists of the synthesis of
spinning motion and coning motion, the modulation characteristics of
its radar returns are more complicated than those of a simple spinning
target. This makes it very difficult to extract accurate micro-motion
features and structure characteristics from the object's radar returns.
In this paper, based on the distributed radar networks, we present an
algorithm for extracting the three-dimensional (3-D) precession features
of cone-shaped space targets. This algorithm takes the advantages of
the multi-view of the distributed radar networks. In the paper, we first
analyze the micro-Doppler (m-D) effect on range-slow-time plane induced
by precession and then present the algorithm step by step, in which
some relevant problems are discussed in detail and, meanwhile, the
respective simulations are given. With aid of the proposed algorithm,
some 3-D precession features and structure characteristics of a target,
such as the 3-D coning vector, spinning period, precession period,
precession angle and the radius of the cone bottom, can be extracted
accurately. The length of the target can also be estimated. In the last
section of the paper, we also give the discussion of the robustness of
the proposed algorithm as well as the respective simulation results.

keywords: {Doppler radar;feature extraction;modulation;3D coning
vector;cone-shaped space targets;coning motion;distributed radar
networks;feature extraction;microDoppler effect;micromotion
features;modulation characteristics;object radar returns;precession
angle;precession period;range-slow-time plane;spinning motion;spinning
period;three-dimensional precession;Educational institutions;Feature
extraction;Imaging;Radar imaging;Spinning;Vectors},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6850157&isnumber=6850134

P.
Lei, J. Wang and J. Sun, "Classification of free rigid targets with
micro-motions using inertial characteristic from radar signatures," in Electronics Letters, vol. 50, no. 13, pp. 950-952, June 19 2014.
doi: 10.1049/el.2014.1091
Abstract:
The potential of an object's inertial characteristic is studied for the
purpose of classification of free rigid targets in radar. Through the
estimation of micro-motion parameters from micro-Doppler signals, the
inertial characteristic can be further obtained. It is an intrinsic
property of the targets themselves, and essentially independent of their
diverse micro-motion states. Then a simple Bayesian classifier is
adopted to make the target discrimination. Numerical results and
analysis finally show that the inertia-based feature performs better
than classic time-frequency and micro-dynamic characteristics in the
classification application.
keywords: {Bayes methods;radar signal
processing;signal classification;time-frequency analysis;classic
time-frequency characteristics;classification application;diverse
micromotion states;free rigid target classification;inertia-based
feature;inertial characteristic;microDoppler signals;microdynamic
characteristics;micromotion parameters;radar signatures;simple Bayesian
classifier;target discrimination},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6838851&isnumber=6838822

Y. He, F. Le Chevalier and A. G. Yarovoy, "Self-similarity analysis on human backscattering in radar," 2013 European Radar Conference, Nuremberg, 2013, pp. 81-84.
Abstract:
The self-similarity of Human target backscattering in radar is
analyzed. The human echo of typical radar signals (i.e., range profiles,
micro-Doppler image and range-Doppler video sequence) is modeled by
motion capture data. Then the self-similarity matrices (SSM) of the
radar signals are constructed and compared. Since the SSM of
range-Doppler video sequence exhibits periodic information in a more
simple manner, it is further analyzed to demonstrate the angle-invariant
characteristic of SSM. Finally, the periodicity of different activities
(i.e., walking and running) are extracted from SSM and compared.

keywords: {Doppler radar;backscatter;gait analysis;radar signal
processing;human backscattering;motion capture data;radar signals;range
Doppler video sequence;self similarity analysis;self similarity
matrices;Doppler effect;Legged locomotion;Radar cross-sections;Radar
imaging;Vectors;Video sequences;gait periodicity;human
backscattering;radar signal;self-similarity},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6689118&isnumber=6689067

Lumin
Shi, Xiongjun Fu, Cai Wang, Ting Li and Meiguo Gao, "The performance
analysis of micro-Doppler extracted from radar echoes under different
bandwidth," IET International Radar Conference 2013, Xi'an, 2013, pp. 1-5.
doi: 10.1049/cp.2013.0294
Abstract:
Sideband Doppler modulation caused by micro motion of targets on radar
echoes is called micro-Doppler effect. Vibration, swing, rotation,
coning, precession and nutation are the most common kinds of micro
motion. In this paper, micro-Doppler is induced by coning motion
mathematically. Then echoes of point scatterers are modelled with linear
frequency modulation (LFM) signal. This paper mainly studies the
performance of micro-Doppler extracted from echoes of targets with
translation compensated completely under different bandwidth. It is more
beneficial to extract micro-Doppler characteristics of each scatterer
respectively as the bandwidth grows wider, when different scatterers can
be separated in range profile domain. At last, the analysis of
performance is verified by simulation.
keywords: {Doppler
radar;modulation;radar cross-sections;radar signal processing;LFM
signal;coning motion;linear frequency modulation;micro
motion;micro-Doppler effect;radar echoes;sideband Doppler
modulation;Micro-motion;bandwidth;linear frequency
modulation;micro-Doppler;radar},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6624458&isnumber=6624271

J. Liu, F. Zhao, Y. Zhang, X. Ai and J. Yang, "Micro-Doppler of non-ideal scattering centers," IET International Radar Conference 2013, Xi'an, 2013, pp. 1-4.
doi: 10.1049/cp.2013.0382
Abstract:
Non-ideal scattering centers exist commonly on radar targets. The
scattering characteristics of them induce additional modulation or
components to the micro-Doppler. Two typical kinds of non-ideal
scattering centers are analyzed and micro-Doppler model of the
scattering centers on the ring structure of precession targets are
introduced as a detailed example. The experimental results demonstrate
the model.
keywords: {electromagnetic wave scattering;military
radar;modulation;radar target recognition;microDoppler
model;modulation;nonideal scattering centers;precession targets;radar
targets;ring structure;scattering
characteristics;Micro-Doppler;Micro-motion;Non-ideal scattering
centers},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6624546&isnumber=6624271

B.
Tekeli, S. Z. Gürbüz, M. Yüksel, A. C. Gürbüz and M. B. Guldogan,
"Classification of human micro-Doppler in a radar network," 2013 IEEE Radar Conference (RadarCon13), Ottawa, ON, 2013, pp. 1-6.
doi: 10.1109/RADAR.2013.6586080
Abstract:
The unique, bi-pedal motion of humans has been shown to generate a
characteristic micro-Doppler signature in the time-frequency domain that
can be used to discriminate humans from not just other targets, but
also between different activities, such as walking and running. However,
the classification performance increasingly drops as the aspect angle
between the target and radar approaches perpendicular, and the radial
velocity component seen by the radar is minimized. In this paper,
exploitation of the multi-static micro-Doppler signature formed from
multi-angle observations of a radar network is proposed to improve
oblique-angle classification performance. The concept of mutual
information is applied to find the order of importance of features for a
given classification problem, thereby enabling the selection of optimal
features prior to classification. Strategies for fusing multistatic
data using mutual information and model-based approaches are discussed.

keywords: {Doppler radar;time-frequency analysis;bipedal motion;human
microDoppler classification;multistatic microDoppler
signature;oblique-angle classification;radar network;radial velocity
component;time-frequency domain;Doppler effect;Feature extraction;Legged
locomotion;Mutual information;Radar;Radar antennas},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6586080&isnumber=6585950

J.
H. Park, I. H. Choi and N. H. Myung, "Modified HHT analysis of
micro-Doppler signatures scattered from rotating flat blades," 2012 International Symposium on Antennas and Propagation (ISAP), Nagoys, 2012, pp. 608-611.
Abstract:
This paper has presented the time-frequency analysis (TFA) of the
micro-Doppler signatures scattered from rotating flat blades using the
modified Hilbert-Huang transform (HHT). After the modified HHT examined
the scattered field data, the analysis results showed good agreement
with real blade numbers in the propeller. It can be concluded that the
TFA via the modified HHT provides the discriminative characteristic for
recognizing a small aircraft target that generally has small radar cross
section (RCS).
keywords: {Doppler radar;Hilbert transforms;airborne
radar;aircraft;blades;propellers;radar cross-sections;radar target
recognition;time-frequency analysis;Hilbert-Huang transform
analysis;aircraft target recognition;microDoppler
signature;propeller;radar cross section;rotating flat
blade;time-frequency analysis;Analytical models;Atmospheric
modeling;Blades;Doppler effect;Propellers;Time frequency
analysis;Transforms},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6394013&isnumber=6393716

P. Lei, J. Sun, J. Wang and W. Hong, "Micromotion Parameter Estimation of Free Rigid Targets Based on Radar Micro-Doppler," in IEEE Transactions on Geoscience and Remote Sensing, vol. 50, no. 10, pp. 3776-3786, Oct. 2012.
doi: 10.1109/TGRS.2012.2185244
Abstract:
In this paper, an estimation method of micromotion parameters for free
rigid targets using micro-Doppler (mD) features is investigated. These
parameters include spin rate, precession rate, nutation angle, and
inertia ratio. They represent the microdynamic characteristics and
intrinsic properties of targets. The time variation of mD frequency is
found complicated yet valuable to estimate the micromotion parameters.
From the viewpoint of the spectra of mixed mD time-frequency (TF) data
sequences, the theoretical analysis and mathematical derivation are
conducted in detail according to the scatterer distribution of rigid
bodies. We then present an approach to realize the micromotion parameter
estimation from radar mD echoes. It mainly consists of TF transform, TF
image processing, mixed mD TF data sequence formation, and spectral
estimation. Simulation experiments and result discussion are carried out
to demonstrate the effectiveness of the proposed estimation method.

keywords: {geophysical techniques;remote sensing by radar;TF image
processing;TF transform;free rigid targets;inertia ratio;micro-Doppler
features;microdynamic characteristics;micromotion parameter
estimation;mixed mD TF data sequence formation;mixed mD time-frequency
data;nutation angle;precession rate;radar microDoppler;spin rate;Doppler
radar;Estimation;Frequency estimation;Frequency modulation;Time
frequency analysis;Inertial characteristics;micro-Doppler
(mD);micromotion parameters;mixed mD TF data sequence},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6166878&isnumber=6310102

O. R. Fogle and B. D. Rigling, "Dismount feature extraction from circular synthetic aperture radar data," 2012 IEEE Radar Conference, Atlanta, GA, 2012, pp. 0122-0127.
doi: 10.1109/RADAR.2012.6212123
Abstract:
Recently, the use of micro-Doppler radar signatures for classification
has become an area of focus, in particular for the case of dynamic
targets where many components are interacting over time. One specific
target of interest is the dismount. Dismount detection, feature
extraction, and classification offers some unique challenges. For
instance, humans have small radar cross-sections and slow range-rates
making discrimination from clutter difficult. Extracted features may be
utilized to distinguish dismounts from other objects, however. In this
paper, range-Doppler radar data collected from an airborne circular
synthetic aperture radar is analyzed to determine extractable dismount
characteristics. The results are compared against high signal-to-clutter
ratio results.^{1 2}
keywords: {Doppler radar;airborne
radar;feature extraction;radar clutter;radar cross-sections;radar
detection;synthetic aperture radar;airborne circular synthetic aperture
radar data;dismount detection;dismount feature extraction;high
signal-to-clutter ratio;microDoppler radar signatures;small radar
cross-sections;Clutter;Doppler effect;Feature extraction;Radar cross
section;Radar imaging;Thyristors},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6212123&isnumber=6212083