Seabed classification and source localization with Gaussian processes and machine learning

Document Type

Article

Publication Date

8-1-2022

Abstract

Workshop '97 data are employed for seabed classification and source range estimation. The data are acoustic fields computed at vertically separated receivers for various ranges and different environments. Gaussian processes are applied for denoising the data and predicting the field at virtual receivers, sampling the water column densely within the array aperture. The enhanced fields are used in combination with machine learning to map the signals to one of 15 sediment-range classes (corresponding to three environments and five ranges). The classification results after using Gaussian processes for denoising are superior to those when noisy workshop data are employed.

Identifier

85147177655 (Scopus)

Publication Title

Jasa Express Letters

External Full Text Location

https://doi.org/10.1121/10.0013365

ISSN

26911191

Issue

8

Volume

2

Grant

N00014-20-1-2029

Fund Ref

Office of Naval Research

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