Sparse Bayesian Synthetic Aperture Processing Based DOA Estimation with Deformed Towed Arrays

In this paper, we present a new synthetic aperture method for direction-of-arrival (DOA) estimation using a passive towed sonar array that is deformed during platform maneuver. With certain prior knowledge of source-array geometry, we propose to find the optimal maximum likelihood estimates of DOAs and sensor positions by maximizing the model evidence of these parameters and the array observations. In order to tackle the resulting complex problem, the variational Bayesian Expectation-Maximization framework is employed. The proposed method is capable of achieving improved angular resolution by aperture synthesis and is robust to perturbations in the array manifold. Numerical simulations illustrate statistical efficiency of the proposed technique.