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Multiperspective micro-Doppler signature classification
IET International Conference on Radar Systems 2007, 2007Multiperspective automatic target recognition is considered to assist underlying classifiers by providing more views of the target. For the first time data from netted radar has been analysed for micro-Doppler signature content and a multiperspective dynamic time warping classifier developed.
G.E. Smith, K. Woodbridge, C.J. Baker
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Person Identification Using Micro-Doppler Signatures of Human Motions and UWB Radar
IEEE Microwave and Wireless Components Letters, 2019 As a typical task of passive biometrics, behavior-based person identification has been studied extensively in recent years. This letter proposes the use of the ultrawideband impulse radar for person identification based upon the micro-Doppler signatures ...
Yang Yang, Yue Lang, Guanghui Yue
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Micro-Doppler Signatures of Small Boats
2014In this chapter, the authors first use the small boats and sea clutter database collected by the Council for Scientific and Industrial Research (CSIR) of South Africa to demonstrate radar microDoppler signatures of small boats in sea clutter. Then, microDoppler images of small boats were compared in the littoral environment.
Victor C. Chen, David Tahmoush
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Acoustic Micro-Doppler Gait Signatures of Humans and Animals
2007 41st Annual Conference on Information Sciences and Systems, 2007A micro-Doppler active acoustic sensing system is described. We report its use in acquiring gait signatures of humans and four-legged animals in indoor and outdoor environments. Signals from an accelerometer attached to the leg support the interpretation of the components in the measured micro-Doppler signature.
Zhaonian Zhang +3 more
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Through-the-Wall Micro-Doppler Signatures
2014Radar technology has been utilized for through-the-wall operation in recent years. Through-the-wall radars have become an area of interest due to their usefulness in surveillance, search and rescue operations, and others. We address the specific challenges that through-the-wall radars endure, and present simulations and experimental data for through ...
Dustin P. Fairchild +4 more
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Signal Decomposition of Micro-Doppler Signatures
2014The micro-Doppler effects detection, estimation, and removal are analyzed in this chapter. Since the most common form of the micro-Doppler signal is a sinusoidal modulated one, a simple technique for its analysis, based on the inverse Radon transform is presented. A method for period estimation is presented as well.
L. Stankovic +3 more
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Radar Micro-Doppler Signature Analysis with HHT
IEEE Transactions on Aerospace and Electronic Systems, 2010Radar micro-Doppler signature analysis of vibrating targets with the joint time-frequency methods can provide useful information for target detection, classification, and recognition. We employ a well-known method for nonlinear and nonstationary signals, Hilbert-Huang transform (HHT) as a new approach in micro-Doppler analysis.
Chengjie Cai +3 more
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Micro-Doppler Signature Extraction with Multibeam Radar
2019 International Radar Conference (RADAR), 2019Orthogonal and quasi-orthogonal waveforms are used in a multibeam radar (MBR) to isolate different channels and reduce cross-channel interference. Each channel provides an independent radar beam that performs a specific functionality without interfering with adjacent channels.
Leon Kocjancic +2 more
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Multistatic Micro-Doppler Signature Processing
2014In this chapter the generation and exploitation of multistatic micro-Doppler radar target signatures are examined with the ultimate aim of improving the classification of targets.
Graeme E. Smith, Christopher J. Baker
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Analytic radar micro-Doppler signatures classification
SPIE Proceedings, 2017Due to its capability of capturing the kinematic properties of a target object, radar micro-Doppler signatures (m-DS) play an important role in radar target classification. This is particularly evident from the remarkable number of research papers published every year on m-DS for various applications.
Beom-Seok Oh +4 more
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