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An image-based approach for classification of human micro-doppler radar signatures

Conference Paper


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Abstract


  • With the advances in radar technology, there is an increasing interest in automatic radar-based human gait identification. This is because radar signals can penetrate through most dielectric materials. In this paper, an image-based approach is proposed for classifying human micro-Doppler radar signatures. The time-varying radar signal is first converted into a time-frequency representation, which is then cast as a two-dimensional image. A descriptor is developed to extract micro-Doppler features from local time-frequency patches centered along the torso Doppler frequency. Experimental results based on real data collected from a 24-GHz Doppler radar showed that the proposed approach achieves promising classification performance.

Publication Date


  • 2013

Citation


  • F. Tivive, S. Phung & A. Bouzerdoum, "An image-based approach for classification of human micro-doppler radar signatures," in Proceedings of SPIE - Active and Passive Signatures IV, 2013, pp. 873406-1-873406-12.

Scopus Eid


  • 2-s2.0-84881172154

Ro Full-text Url


  • http://ro.uow.edu.au/cgi/viewcontent.cgi?article=2605&context=eispapers

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers/1596

Start Page


  • 873406-1

End Page


  • 873406-12

Abstract


  • With the advances in radar technology, there is an increasing interest in automatic radar-based human gait identification. This is because radar signals can penetrate through most dielectric materials. In this paper, an image-based approach is proposed for classifying human micro-Doppler radar signatures. The time-varying radar signal is first converted into a time-frequency representation, which is then cast as a two-dimensional image. A descriptor is developed to extract micro-Doppler features from local time-frequency patches centered along the torso Doppler frequency. Experimental results based on real data collected from a 24-GHz Doppler radar showed that the proposed approach achieves promising classification performance.

Publication Date


  • 2013

Citation


  • F. Tivive, S. Phung & A. Bouzerdoum, "An image-based approach for classification of human micro-doppler radar signatures," in Proceedings of SPIE - Active and Passive Signatures IV, 2013, pp. 873406-1-873406-12.

Scopus Eid


  • 2-s2.0-84881172154

Ro Full-text Url


  • http://ro.uow.edu.au/cgi/viewcontent.cgi?article=2605&context=eispapers

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers/1596

Start Page


  • 873406-1

End Page


  • 873406-12