Northwest Electromagnetics and Acoustics Lab (NEAR-Lab) Colloquium
Author: Adaptive Beamforming for Sonar
Posted: April 20, 2012

TITLE: Adaptive Beamforming for Sonar
PRESENTER: D. A. Abraham, CausaSci LLC

Many applications in remote sensing entail the analysis of waves propagating from a signal of interest as measured by an array of spatially separated sensors.  Spatial filtering, known as beamforming, is a common means for increasing signal-to-noise ratio (SNR), rejecting interferences, and localizing a signal.  Conventional beamforming (CBF) concepts are largely similar to their classical spectral-estimation counterparts.  This seminar introduces the basic concepts of what is known as adaptive beamforming (ABF) where, similar to data-adaptive spectral estimation, the spatial filter is designed according to the second-order spatial statistics of the array data.  The primary application considered is array processing for passive sonar.

In contrast to CBF where the spatial filters are fixed, ABF can exploit data-derived information such as the bearing of an interfering signal and produce a spatial filter with a null in its direction, thereby improving performance in other directions.  The impact on the beam pattern (i.e., filter transfer function), beam response (i.e., filter output), and white-noise gain is investigated for a side-lobe canceller and a minimum-variance-distortionless-response beamformer.  The cost of the improved performance attainable by ABF is a requirement to estimate the covariance matrix of the array data.  The loss in performance arising from covariance-matrix estimation is quantified by a (random) loss in SNR.  Finally, an example application to passive sonar is presented, illustrating the benefits of ABF over CBF.

D. A. Abraham obtained B.S., M.S., and Ph.D. degrees in Electrical Engineering and an M.S. degree in Statistics from the University of Connecticut. He has over twenty years of experience in the sonar field, having held positions at U.S. Navy, NATO, and University laboratories. His research has primarily been in applying detection and estimation theory to active and passive sonar signal processing problems. He has both undergraduate and graduate teaching experience at the Electrical and Computer Engineering Department of the University of Connecticut. He has managed basic and applied research programs at the Office of Naval Research and has been active in professional service through technical-committee membership, conference and workshop organization, and as an associate editor of the IEEE Journal of Oceanic Engineering.