A New Statistical Model for Waveguide Invariant-Based Range Estimation in Shallow Water
Abstract
Navigation and source localization in the undersea environment are challenged by the absence of a ubiquitous positioning system. Passive acoustic ranging offers a valuable means of obtaining location information underwater. We present a range estimation method based on waveguide invariant (WI) theory, using ship noise recorded by a hydrophone as an acoustic source. The WI is a scalar parameter that describes the interference patterns in spectrograms caused by the interaction of acoustic wave modes propagating in a waveguide, such as shallow water. WI theory enables ranging using a single receiver without detailed knowledge of the environment. In this paper, underwater acoustic signals radiated by a moving large ship, which include broadband and tonal components, are employed for WI-based ranging in a range-independent shallow water environment. In particular, we develop a likelihood function for WI-based range estimation by introducing a statistical model for high signal-to-noise ratio scenarios. Here, the broadband component is assumed to dominate the background noise. The effectiveness of the proposed range estimation method is demonstrated using real acoustic measurements of a moving container ship recorded during the Seabed Characterization Experiment 2017 (SBCEX17).
Keywords
Cite
@article{arxiv.2412.02201,
title = {A New Statistical Model for Waveguide Invariant-Based Range Estimation in Shallow Water},
author = {Junsu Jang and Florian Meyer},
journal= {arXiv preprint arXiv:2412.02201},
year = {2024}
}