Estimation of the spatial variability of the New England Mud Patch geoacoustic properties using a distributed array of hydrophones and deep learning
Name
4229_1_10.0034707.pdf
Description
Published version
Size
6.68 MB
Format
Adobe PDF
Checksum (MD5)
dac2c342c36d652c8be37bfcc686aea2
Author(s)
Vardi, Ariel
Dahl, Peter H
Dall'Osto, David
Knobles, David
Wilson, Preston
Leonard, John
Bonnel, Julien
Date Issued
December 6, 2024
Journal
The Journal of the Acoustical Society of America
Publisher
Acoustical Society of America
Citation
Ariel Vardi, Peter H. Dahl, David Dall'Osto, David Knobles, Preston Wilson, John Leonard, Julien Bonnel; Estimation of the spatial variability of the New England Mud Patch geoacoustic properties using a distributed array of hydrophones and deep learning. J. Acoust. Soc. Am. 1 December 2024; 156 (6): 4229–4241.
Version
Final published version
Abstract
This article presents a spatial environmental inversion scheme using broadband impulse signals with deep learning (DL) to model a single spatially-varying sediment layer over a fixed basement. The method is applied to data from the Seabed Characterization Experiment 2022 (SBCEX22) in the New England Mud-Patch (NEMP). Signal Underwater Sound (SUS) explosive charges generated impulsive signals recorded by a distributed array of bottom-moored hydrophones. The inversion scheme is first validated on a range-dependent synthetic test set simulating SBCEX22 conditions, then applied to experimental data to predict the lateral spatial structure of sediment sound speed and its ratio with the interfacial water sound speed. Traditional geoacoustic inversion requires significant computational resources. Here, a neural network enables rapid single-signal inversion, allowing the processing of 1836 signals along 722 tracks. The method is applied to both synthetic and experimental data. Results from experimental data suggest an increase in both absolute compressional sound speed and sound speed ratio from southwest to northeast in the NEMP, consistent with published coring surveys and geoacoustic inversion results. This approach demonstrates the potential of DL for efficient spatial geoacoustic inversion in shallow water environments.
MIT Department
Joint Program in Applied Ocean Physics and Engineering
Massachusetts Institute of Technology. Department of Mechanical Engineering
Terms of Use
Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
Persistent DSpace Link
DOI of Published Version
10.1121/10.0034707
