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Self-similarity matrix based slow-time feature extraction for human target in high-resolution radar

Published online by Cambridge University Press:  25 March 2014

Yuan He Open the ORCID record for Yuan He [Opens in a new window] ,
Pascal Aubry ,
Francois Le Chevalier Open the ORCID record for Francois Le Chevalier [Opens in a new window]  and
Alexander Yarovoy
Yuan He*
Affiliation:
Microwave sensing, signals and systems (MS3), Delft University of Technology, Delft, The Netherlands. Phone: +31 15 2788378
Pascal Aubry
Affiliation:
Microwave sensing, signals and systems (MS3), Delft University of Technology, Delft, The Netherlands. Phone: +31 15 2788378
Francois Le Chevalier
Affiliation:
Microwave sensing, signals and systems (MS3), Delft University of Technology, Delft, The Netherlands. Phone: +31 15 2788378
Alexander Yarovoy
Affiliation:
Microwave sensing, signals and systems (MS3), Delft University of Technology, Delft, The Netherlands. Phone: +31 15 2788378
*
Corresponding author: Y. He Email: [email protected]
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Abstract

A new approach is proposed to extract the slow-time feature of human motion in high-resolution radars. The approach is based on the self-similarity matrix (SSM) of the radar signals. The Mutual Information is used as a measure of similarity. The SSMs of different radar signals (high-resolution range profile, micro-Doppler, and range-Doppler video sequence) are compared, and the angel-invariant property of the SSMs is demonstrated. The SSM for different activities (i.e. walking and running) is extracted from range-Doppler video sequence and analyzed. Finally, simulation result is validated by experimental data.

Keywords

Self-similarity matrixSlow-time featureHuman target analysisHigh-resolution radar
Type
Research Paper
Information
International Journal of Microwave and Wireless Technologies , Volume 6 , Issue 3-4: European Microwave Week 2013 , June 2014 , pp. 423 - 434
Copyright
Copyright © Cambridge University Press and the European Microwave Association 2014 

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