Multi-Aspect Angle Classification of Human Radar Signatures
Küçük Resim Yok
Tarih
2013
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Spie-Int Soc Optical Engineering
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
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 time-frequency 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.
Açıklama
Conference on Active and Passive Signatures IV -- MAY 01-02, 2013 -- Baltimore, MD
Anahtar Kelimeler
human micro-Doppler; human classification; data fusion; radar networks
Kaynak
Active And Passive Signatures Iv
WoS Q Değeri
N/A
Scopus Q Değeri
Q4
Cilt
8734
