Hilbert-Huang transform (HHT) processing of through-wall noise radar data for human activity characterization

Chieh Ping Lai, Qing Ruan, Ram Mohan Narayanan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

15 Citations (Scopus)

Abstract

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.

Original languageEnglish (US)
Title of host publicationProceedings - SAFE 2007
Subtitle of host publicationWorkshop on Signal Processing Applications for Public Security and Forensics
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)1424412269, 9781424412266
StatePublished - Jan 1 2007
EventWorkshop on Signal Processing Applications for Public Security and Forensics, SAFE 2007 - Washington, United States
Duration: Apr 11 2007Apr 13 2007

Publication series

NameProceedings - SAFE 2007: Workshop on Signal Processing Applications for Public Security and Forensics

Other

OtherWorkshop on Signal Processing Applications for Public Security and Forensics, SAFE 2007
CountryUnited States
CityWashington
Period4/11/074/13/07

Fingerprint

Spurious signal noise
Wigner-Ville distribution
Terrorism
Wavelet analysis
Radar systems
Ultra-wideband (UWB)
Pattern recognition
Fourier transforms
Signal processing
Radar
Processing
pattern recognition
interference
terrorism
human being
time

All Science Journal Classification (ASJC) codes

  • Law
  • Computer Vision and Pattern Recognition
  • Signal Processing

Cite this

Lai, C. P., Ruan, Q., & Narayanan, R. M. (2007). Hilbert-Huang transform (HHT) processing of through-wall noise radar data for human activity characterization. In Proceedings - SAFE 2007: Workshop on Signal Processing Applications for Public Security and Forensics [4218957] (Proceedings - SAFE 2007: Workshop on Signal Processing Applications for Public Security and Forensics). Institute of Electrical and Electronics Engineers Inc..
Lai, Chieh Ping ; Ruan, Qing ; Narayanan, Ram Mohan. / Hilbert-Huang transform (HHT) processing of through-wall noise radar data for human activity characterization. Proceedings - SAFE 2007: Workshop on Signal Processing Applications for Public Security and Forensics. Institute of Electrical and Electronics Engineers Inc., 2007. (Proceedings - SAFE 2007: Workshop on Signal Processing Applications for Public Security and Forensics).
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Lai, CP, Ruan, Q & Narayanan, RM 2007, Hilbert-Huang transform (HHT) processing of through-wall noise radar data for human activity characterization. in Proceedings - SAFE 2007: Workshop on Signal Processing Applications for Public Security and Forensics., 4218957, Proceedings - SAFE 2007: Workshop on Signal Processing Applications for Public Security and Forensics, Institute of Electrical and Electronics Engineers Inc., Workshop on Signal Processing Applications for Public Security and Forensics, SAFE 2007, Washington, United States, 4/11/07.

Hilbert-Huang transform (HHT) processing of through-wall noise radar data for human activity characterization. / Lai, Chieh Ping; Ruan, Qing; Narayanan, Ram Mohan.

Proceedings - SAFE 2007: Workshop on Signal Processing Applications for Public Security and Forensics. Institute of Electrical and Electronics Engineers Inc., 2007. 4218957 (Proceedings - SAFE 2007: Workshop on Signal Processing Applications for Public Security and Forensics).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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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.

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M3 - Conference contribution

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Lai CP, Ruan Q, Narayanan RM. Hilbert-Huang transform (HHT) processing of through-wall noise radar data for human activity characterization. In Proceedings - SAFE 2007: Workshop on Signal Processing Applications for Public Security and Forensics. Institute of Electrical and Electronics Engineers Inc. 2007. 4218957. (Proceedings - SAFE 2007: Workshop on Signal Processing Applications for Public Security and Forensics).