TY - GEN
T1 - Hilbert-Huang transform (HHT) processing of through-wall noise radar data for human activity characterization
AU - Lai, Chieh Ping
AU - Ruan, Qing
AU - Narayanan, Ram M.
N1 - Funding Information:
This research was supported by the U.S. Air Force Office of Scientific Research (AFOSR) STTR Contract # FA9550-06-C-0101 through Intelligent Automation, Inc. (IAI). We appreciate fruitful comments and suggestions by Dr. A. Nachman of AFOSR, Dr. R. Albanese of Air Force Research Laboratory (AFRL), and Dr. A. Davydov of IAI.
Publisher Copyright:
© 2007 IEEE.
PY - 2007
Y1 - 2007
N2 - Different parts of the human body have different movements when a person is performing different physical activities. Also, there is great interest to remotely detect human heartbeat and breathing for applications involving anti-terrorism and search-and-rescue. Ultrawideband noise radar systems are attractive because they are covert and immune from interference. The conventional time-frequency analyses of human activity (usually including the short time Fourier transform (STFT), Wigner-Ville distribution (WVD), and wavelet analysis) are not generally adaptive to nonlinear and nonstationary signals. If one can decompose the noisy baseband signal containing human Doppler information and extract only the human-induced Doppler from it, the identification of various human activities becomes easier. We therefore propose to use a recently developed method, the Hilbert-Huang transform (HHT), since it is adaptive to nonlinear and nonstationary signals. When used with noise-like radar data, it is useful for covert detection of human movement. The HHT based signal processing can effectively improve pattern recognition and reject unwanted uncorrelated noise.
AB - Different parts of the human body have different movements when a person is performing different physical activities. Also, there is great interest to remotely detect human heartbeat and breathing for applications involving anti-terrorism and search-and-rescue. Ultrawideband noise radar systems are attractive because they are covert and immune from interference. The conventional time-frequency analyses of human activity (usually including the short time Fourier transform (STFT), Wigner-Ville distribution (WVD), and wavelet analysis) are not generally adaptive to nonlinear and nonstationary signals. If one can decompose the noisy baseband signal containing human Doppler information and extract only the human-induced Doppler from it, the identification of various human activities becomes easier. We therefore propose to use a recently developed method, the Hilbert-Huang transform (HHT), since it is adaptive to nonlinear and nonstationary signals. When used with noise-like radar data, it is useful for covert detection of human movement. The HHT based signal processing can effectively improve pattern recognition and reject unwanted uncorrelated noise.
UR - https://www.scopus.com/pages/publications/84969135118
UR - https://www.scopus.com/pages/publications/84969135118#tab=citedBy
M3 - Conference contribution
AN - SCOPUS:84969135118
T3 - Proceedings - SAFE 2007: Workshop on Signal Processing Applications for Public Security and Forensics
BT - Proceedings - SAFE 2007
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - Workshop on Signal Processing Applications for Public Security and Forensics, SAFE 2007
Y2 - 11 April 2007 through 13 April 2007
ER -
