A Probabilistic Focalization Approach for Single Receiver Underwater Localization

TL;DR

This paper presents a Bayesian probabilistic method for localizing acoustic sources underwater with a single receiver, effectively handling measurement uncertainty and demonstrating promising results with real data.

Contribution

It introduces a novel probabilistic focalization approach that estimates source location in shallow water using a single mobile receiver and probabilistic data association.

Findings

Effective localization of underwater acoustic sources demonstrated with real data.

Handles measurement-origin uncertainty through probabilistic data association.

Outperforms traditional methods in accuracy and robustness.

Abstract

We introduce a Bayesian estimation approach for the passive localization of an acoustic source in shallow water using a single mobile receiver. The proposed probabilistic focalization method estimates the time-varying source location in the presence of measurement-origin uncertainty. In particular, probabilistic data association is performed to match time-differences-of-arrival (TDOA) observations extracted from the acoustic signal to TDOAs predictions provided by the statistical model. The performance of our approach is evaluated using real acoustic data recorded by a single mobile receiver.