Acoustic Source Localization in Shallow Water: A Probabilistic Focalization Approach

TL;DR

This paper introduces a Bayesian probabilistic focalization method for localizing acoustic sources in shallow water, leveraging environmental modeling and DOA data to improve accuracy over traditional matched field processing.

Contribution

It develops a novel Bayesian approach that integrates environmental parameters via embedded ray tracing for improved source localization in shallow water.

Findings

Outperforms matched field processing in SWellEx-96 data

Effectively incorporates environmental parameters

Provides accurate time-varying source localization

Abstract

This paper presents a Bayesian estimation method for the passive localization of an acoustic source in shallow water. Our probabilistic focalization approach estimates the time-varying source location by associating direction of arrival (DOA) observations to DOAs predicted based on a statistical model. Embedded ray tracing makes it possible to incorporate environmental parameters and characterize the nonlinear acoustic waveguide. We demonstrate performance advantages of our approach compared to matched field processing using data collected during the SWellEx-96 experiment.