Issues in acoustic vector-sensor processing

This dissertation examines the ability of acoustic vector sensors to solve the passive direction-of-arrival (DOA) estimation and 3-D localization problems. These sensors measure the three-dimensional acoustic particle velocity vector, as well as the acoustic pressure, at one location. By preserving directional information that is present in the structure of the velocity field, they gain a number of advantages over traditional arrays of scalar sensors, such as hydrophones and microphones. We compute and examine, through the Cramer-Rao bound and beam-forming based methods, the ability of arrays of acoustic vector sensors to estimate direction. We first consider the case of an array in free space then extend these results to account for the presence of a reflecting boundary, such as the seabed or a vessel's hull, located near the array. Next, we derive expressions for the noise correlation structure induced by various ambient noise fields, isotropic and anisotropic, at an acoustic vector sensor array, and use them to examine its localization performance. We then propose a decentralized processing scheme to rapidly locate a wideband target in three dimensions. Finally, we present a general framework for the analysis of errors associated with the estimation of a vector, or system of vectors, that has geometrical interpretations in terms of length, angle, etc. The framework is employed throughout the thesis.