Histogram Layer Time Delay Neural Networks for Passive Sonar Classification

Jarin Ritu, Ethan Barnes, Riley Martell, Alexandra Van Dine, Joshua Peeples
7/25/2023
cs.SDcs.LGeess.AS

Official code: Advanced-Vision-and-Learning-Lab/HLTDNN (19 stars, MIT, last commit 2026-01-21).

Abstract

Underwater acoustic target detection in remote marine sensing operations is challenging due to complex sound wave propagation. Despite the availability of reliable sonar systems, target recognition remains a difficult problem. Various methods address improved target recognition. However, most struggle to disentangle the high-dimensional, non-linear patterns in the observed target recordings. In this work, a novel method combines a time delay neural network and histogram layer to incorporate statistical contexts for improved feature learning and underwater acoustic target classification. The proposed method outperforms the baseline model, demonstrating the utility in incorporating statistical contexts for passive sonar target recognition. The code for this work is publicly available.

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Code Implementations(1)

Advanced-Vision-and-Learning-Lab/HLTDNNOfficial
MIT

Histogram Layer Time Delay Neural Networks For Passive Sonar Classification

194PythonMay 24, 20239 months agoMIT

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Cite this paper

@article{ritu2023histogram,
  title  = {Histogram Layer Time Delay Neural Networks for Passive Sonar Classification},
  author = {Jarin Ritu and Ethan Barnes and Riley Martell and Alexandra Van Dine and Joshua Peeples},
  year   = {2023},
  eprint = {2307.13788},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2307.13788v1}
}

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