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Underwater Small Target Classification Using Sparse Multi-View Discriminant Analysis and the Invariant Scattering Transform.

Authors :
Christensen, Andrew
Sen Gupta, Ananya
Kirsteins, Ivars
Source :
Journal of Marine Science & Engineering; Oct2024, Vol. 12 Issue 10, p1886, 32p
Publication Year :
2024

Abstract

Sonar automatic target recognition (ATR) systems suffer from complex acoustic scattering, background clutter, and waveguide effects that are ever-present in the ocean. Traditional signal processing techniques often struggle to distinguish targets when noise and complicated target geometries are introduced. Recent advancements in machine learning and wavelet theory offer promising directions for extracting informative features from sonar return data. This work introduces a feature extraction and dimensionality reduction technique using the invariant scattering transform and Sparse Multi-view Discriminant Analysis for identifying highly informative features in the PONDEX09/PONDEX10 datasets. The extracted features are used to train a support vector machine classifier that achieves an average classification accuracy of 97.3% using six unique targets. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20771312
Volume :
12
Issue :
10
Database :
Complementary Index
Journal :
Journal of Marine Science & Engineering
Publication Type :
Academic Journal
Accession number :
180529393
Full Text :
https://doi.org/10.3390/jmse12101886