Blind separation of signal and multipath interference for synthetic aperture sonar

Multipath interference is a major source of noise for synthetic aperture sonar systems operating in shallow water. Motivated by this problem, we present an iterative algorithm for blindly separating the signal from the multipath interference that uses differences in the temporal coherence properties of the signal and multipaths caused by sea surface roughness to estimate the optimum filter weights. The filter weights are estimated by minimizing the circular variance of the phase differences between overlapping vertical phase centers. An important advantage of this approach is that signal-free training data and accurate array calibration information are not needed. Experimentally we show that the blind separation performance is competitive with high resolution angle of arrival estimation and compares favorably to the Cramer-Rao lower bound predicted error.