Broyden-Fletcher-Goldfarb-Shanno methods with application to underwater acoustic beamforming

Abstract

This paper proposes the linearly constrained minimum variance (LCMV) beamforming method based on steepest descent (SD) and Broyden-Fletcher-Goldfarb-Shanno (BFGS) methods for underwater acoustic beamforming. The proposed methods avoid the covariance matrix inversion operation and the eigenvalue decomposition for variable diagonal loading in the conventional LCMV beamforming, which avails the efficiency of beamforming, and the required operations are significantly reduced. The simulation results show that the improved methods own better recognition ability for the target signals and suppression ability for the interference signals.