Communication Dans Un Congrès Année : 2025

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

Résumé

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.

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Dates et versions

hal-05211702 , version 1 (16-08-2025)

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  • HAL Id : hal-05211702 , version 1

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Soggia Antonio, Lionel Fillatre, Deruaz-Pepin Laurent. A Lightweight CNN for Noise Source Detection in Bearing-Time Sonar images. EUSIPCO 2025, Sep 2025, PALERMO, Italy. ⟨hal-05211702⟩
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