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Proceedings Paper

Space-time beamforming for randomly distributed sensors
Author(s): Kung Yao; Ralph E. Hudson; C. W. Reed; Datong Chen; Tai-Lai Tung; Flavio Lorenzelli
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Paper Abstract

We briefly review the signal processing architecture of a wireless MEM sensor system for source detection, signal enhancement, localization, and identification. A blind beamformer using only the measured data of randomly distributed sensor to form a sample correlation matrix is proposed. The maximum power collection criterion is used to obtain array weights from the dominant eigenvector of the sample correlation matrix. An effective blind beamforming estimation of the time delays of the dominant source is demonstrated. Source localization based on a novel least-squares method for time delay estimation is also given. Array system performance based on analysis, simulation, and measured acoustical/seismic sensor data is presented. Applications of such a system to multimedia, intrusion detection, and surveillance are briefly discussed.

Paper Details

Date Published: 2 October 1998
PDF: 10 pages
Proc. SPIE 3461, Advanced Signal Processing Algorithms, Architectures, and Implementations VIII, (2 October 1998); doi: 10.1117/12.325686
Show Author Affiliations
Kung Yao, Univ. of California/Los Angeles (United States)
Ralph E. Hudson, Univ. of California/Los Angeles (United States)
C. W. Reed, Univ. of California/Los Angeles (United States)
Datong Chen, Univ. of California/Los Angeles (United States)
Tai-Lai Tung, Univ. of California/Los Angeles (United States)
Flavio Lorenzelli, Univ. of California/Los Angeles (United States)


Published in SPIE Proceedings Vol. 3461:
Advanced Signal Processing Algorithms, Architectures, and Implementations VIII
Franklin T. Luk, Editor(s)

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