Estimating the Motion Parameters of Sound Sources Using a Network of Compact Arrays

In this article, the problem of employing passive acoustics to estimate the position, speed, and heading angle of a moving source using a network of underwater compact arrays is considered. Maximum-likelihood (ML) estimators using angle-of-arrival (AOA), time-difference-of-arrival (TDOA), and a combination of AOA/TDOA estimates are developed. The estimation accuracy provided by the AOA-based, TDOA-based, and hybrid estimators is evaluated using Cramer-Rao bounds (CRB), statistical simulations, and an in situ test. Test results demonstrate that practical accuracy provided by the proposed algorithms strongly depends on deviations in speed and heading angles from their average values.