Space-time beamforming for randomly distributed sensors

Kung Yao; Ralph E. Hudson; C. W. Reed; Datong Chen; Tai-Lai Tung; Flavio Lorenzelli

doi:10.1117/12.325686

2 October 1998 Space-time beamforming for randomly distributed sensors

Kung Yao, Ralph E. Hudson, C. W. Reed, Datong Chen, Tai-Lai Tung, Flavio Lorenzelli

Proceedings Volume 3461, Advanced Signal Processing Algorithms, Architectures, and Implementations VIII; (1998) https://doi.org/10.1117/12.325686
Event: SPIE's International Symposium on Optical Science, Engineering, and Instrumentation, 1998, San Diego, CA, United States

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.

Citation Download Citation

Kung Yao, Ralph E. Hudson, C. W. Reed, Datong Chen, Tai-Lai Tung, and Flavio Lorenzelli "Space-time beamforming for randomly distributed sensors", Proc. SPIE 3461, Advanced Signal Processing Algorithms, Architectures, and Implementations VIII, (2 October 1998); https://doi.org/10.1117/12.325686

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