Abstract
Lisa Zurk’s numerous contributions to passive sonar signal processing include motion compensation and regularizing sample covariance matrices (SCM) in snapshot deficient environments. While working at MIT Lincoln Labs, Lisa and colleagues compared the performance of several motion compensation methods including mode-based rank reduction and target motion compensation, or focusing, on the Santa Barbara Channel Experiment dataset [Zurk, Lee & Ward, JASA, 2003]. Later at Portland State, Jorge Quijano and Lisa developed methods for regularizing the SCM through Toeplitz averaging, followed by maximum entropy extrapolation of the SCM to additional lags, [Quijano & Zurk, JASA, 2017]. Toeplitz regularization found significant application in developing “augmented covariance matrices” for DOA estimators on sparse arrays. This talk reviews some of Lisa’s contributions to adaptive beamforming and highlights how some of her contributions inspired research in the UMass Dartmouth Signal Processing Group. [Work supported by ONR Code 321US.]