Work

A Lightweight CNN for Noise Source Detection in Bearing-Time Sonar Images

Year: 2025

Type: conference-paper

Abstract: In current broadband passive sonar systems, a human operator observes a series of sonar measurements that represents different energy levels in the bearing and time dimensions. Detecting weak noise sources amidst ambient sea noise can be challenging. This paper proposes a lightweight neural network based on U-Net that detects the presence of low SNR noise sources in a multipath setting. The architecture we designed predict only the direct path. Then, a linear detector can detect efficiently the presence of the acoustic source from the enhanced direct path.

Source: European Signal Processing Conference (EUSIPCO)

DOI: 10.23919/eusipco63237.2025.11226049

Authors: Soggia Antonio, Fillatre Lionel, Deruaz-Pepin Laurent

Institutions: Laboratoire d'Informatique, Signaux et Systèmes de Sophia Antipolis, Centre National de la Recherche Scientifique, Thales (France)

Language: English

Topic: Underwater Acoustics Research

Subfield: Oceanography

Field: Earth and Planetary Sciences

Domain: Physical Sciences

Open Access status: green

Funder: Association Nationale de la Recherche et de la Technologie

OpenAlex ID: W4414588184

FWCI:

Cites:

Cited by:

Related to: