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Proceedings Paper

Multi-aspect angle classification of human radar signatures
Author(s): C. Karabacak; S. Z. Gürbüz; M. B. Guldogan; A. C. Gürbüz
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Paper Abstract

The human micro-Doppler signature is a unique signature caused by the time-varying motion of each point on the human body, which can be used to discriminate humans from other targets exhibiting micro-Doppler, such as vehicles, tanks, helicopters, and even other animals. Classification of targets based on micro-Doppler generally involves joint timefrequency analysis of the radar return coupled with extraction of features that may be used to identify the target. Although many techniques have been investigated, including artificial neural networks and support vector machines, almost all suffer a drastic drop in classification performance as the aspect angle of human motion relative to the radar increases. This paper focuses on the use of radar networks to obtain multi-aspect angle data and thereby ameliorate the dependence of classification performance on aspect angle. Knowledge of human walking kinematics is exploited to generate a fuse spectrogram that incorporates estimates of model parameters obtained from each radar in the network. It is shown that the fused spectrogram better approximates the truly underlying motion of the target observed as compared with spectrograms generated from individual nodes.

Paper Details

Date Published: 23 May 2013
PDF: 10 pages
Proc. SPIE 8734, Active and Passive Signatures IV, 873408 (23 May 2013); doi: 10.1117/12.2017709
Show Author Affiliations
C. Karabacak, TOBB Univ. of Economics and Technology (Turkey)
S. Z. Gürbüz, TOBB Univ. of Economics and Technology (Turkey)
TUBITAK Space Technologies Research Institute (Turkey)
M. B. Guldogan, Turgut Ozal Univ. (Turkey)
A. C. Gürbüz, TOBB Univ. of Economics and Technology (Turkey)


Published in SPIE Proceedings Vol. 8734:
Active and Passive Signatures IV
G. Charmaine Gilbreath; Chadwick Todd Hawley, Editor(s)

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