Automated approach for recovering modal components in shallow waters

International audience This paper proposes a fully automated method for recovering modal components from a signal in shallow waters. The scenario involves an unknown source emitting low-frequency sound waves in a shallow water environment, and a single hydrophone recording the signal. The proposed a...

Full description

Bibliographic Details
Published in:The Journal of the Acoustical Society of America
Main Authors: Niclas, Angèle, Garnier, Josselin
Other Authors: Centre de Mathématiques Appliquées de l'Ecole polytechnique (CMAP), École polytechnique (X), Institut Polytechnique de Paris (IP Paris)-Institut Polytechnique de Paris (IP Paris)-Centre National de la Recherche Scientifique (CNRS), Analyse d’interactions stochastiques intelligentes et coopératives (ASCII), Institut Polytechnique de Paris (IP Paris)-Institut Polytechnique de Paris (IP Paris)-Centre National de la Recherche Scientifique (CNRS)-École polytechnique (X), Institut Polytechnique de Paris (IP Paris)-Institut Polytechnique de Paris (IP Paris)-Centre National de la Recherche Scientifique (CNRS)-Inria Saclay - Ile de France, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)
Format: Article in Journal/Newspaper
Language:English
Published: HAL CCSD 2024
Subjects:
Online Access:https://hal.science/hal-04686158
https://doi.org/10.1121/10.0025471
Description
Summary:International audience This paper proposes a fully automated method for recovering modal components from a signal in shallow waters. The scenario involves an unknown source emitting low-frequency sound waves in a shallow water environment, and a single hydrophone recording the signal. The proposed automated algorithm is based on the warping method to separate each modal component in the time-frequency space. However, instead of manually choosing a single arrival time for extraction, the method performs successive extractions with automated time selection based on an explicit quality factor. Modal component separation is achieved through a watershed algorithm, streamlining the process and eliminating the need for manual intervention. The proposed method is tested on experimental data of a right whale gunshot, a combustive sound source, and a bowhead whale upsweep, demonstrating its effectiveness in real-world scenarios.