Underwater three-dimensional source localization in non-Gaussian noise using acoustic vector sensor array

A computationally efficient method of three-dimensional (3-D) localization of underwater acoustic sources using an acoustic vector sensor (AVS) array is presented in this paper. Noise is modeled as a Gaussian mixture (GM), and an expectation maximization (EM) algorithm is used to estimate all the unknown parameters. The proposed method consists of an initialization stage followed by iterative updates which converge in a small number of iterations. Performance of the proposed method is better than that of existing methods, and performance of the AVS array is much better than that of the acoustic pressure sensor (APS) array.