学术报告

Title: Analysis, Design, and Implementation of Beamforming in Wireless Sensor Networks

Speaker: Prof. Kung Yao

Distinguished Professor, Electrical Engineering Department University of California Los Angeles (UCLA)

Time: April. 03, 2007, 10:30AM

Place: 1-315, FIT Building

Organizer: Research Institute of Information Technology (RIIT), Tsinghua University

Kung Yao received the B.S.E. (Highest Honors), M.A. and Ph.D. degrees in electrical engineering all from Princeton University, Princeton, N.J. Presently, he is a Distinguished Professor in the Electrical Engineering Department at UCLA. In 1985-1988, he served as an Assistant Dean of the School of Engineering and Applied Science at UCLA. His research interests include sensor array system, digital communication theory, wireless radio system, digital and array processing, systolic and VLSI algorithms. He has published over 250 journal and conference papers. Dr. Yao received the IEEE Signal Processing Society's 1993 Senior Award in VLSI Signal Processing. He was the co-editor of a two volume series of an IEEE Reprint Book on "High Performance VLSI Signal Processing," IEEE Press, 1997. He has served as Associate Editors for IEEE Transactions on Information Theory, IEEE Transactions on Signal Processing, IEEE Transactions on Circuits and Systems, IEEE Communications Letters, and guest editors of numerous Special Issues. He is a Life Fellow of IEEE.

In this overview talk, we will review three different classes of acoustical beamforming in sensor networks. The first array used four uniformly-spaced hearing aid microphones to perform a steerable array based on the maximum-energy criterion. A system implemented with a DSP processor board collected various experimental data in an anechoic chamber and a regular room for hearing aid applications. The second array used randomly distributed microphones to perform wideband beamforming based on a maximum eigenvector array for vehicle detection, localization, and signal enhancement. The third array was based on the Approximate Maximum-Likelihood criterion to estimate single or multiple acoustic sources for near-field localization and far-field direction-of-arrival estimations. This array was capable of various beamforming and nulling operations. Several wired and wireless experimental arrays have been implemented for various applications.