Underwater Target Detection and Localization with Feature Map and CNN-Based Classification

Tiantian Guo, Yunze Song, Zejian Kong, Enggee Lim, Miguel Lopez-Benitez, Fei Ma, Limin Yu*

*Corresponding author for this work

Research output: Chapter in Book or Report/Conference proceedingConference Proceedingpeer-review

5 Citations (Scopus)

Abstract

The purpose of this paper is to apply the acoustic features, Mel Frequency Cepstral Coefficient (MFCC) and Gammatone Frequency Cepstral Coefficient (GFCC), to underwater signal classification. Underwater acoustic signals are vibration signals, and their characteristics are similar to speech signals. The auditory feature extraction method in speech recognition can also be applied to the underwater environment. For underwater communication, we simulate two models designed for underwater target detection and localization. One is the deterministic model, which is considered as basic model; the other is to combine the deterministic model and statistic model, which is called combined model. The geometric channel model facilitates the generation of the database for different geometric settings. The database is generated by adjusting the parameters of the underwater environment. The classifier adopts a convolutional neural network (CNN). The input to the CNN is the feature maps after feature extraction. We choose continuous wavelet transform (CWT) and short-time Fourier transform (STFT) for comparison. Experiments show the effectiveness of the system architecture and superiority of the proposed algorithm in underwater signal classification and target localization.

Original languageEnglish
Title of host publicationCTISC 2022 - 2022 4th International Conference on Advances in Computer Technology, Information Science and Communications
EditorsVassilis C. Gerogianni, Yong Yue, Fairouz Kamareddine
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665458726
DOIs
Publication statusPublished - 22 Apr 2022
Event4th International Conference on Advances in Computer Technology, Information Science and Communications, CTISC 2022 - Suzhou, China
Duration: 22 Apr 202224 Apr 2022

Publication series

NameCTISC 2022 - 2022 4th International Conference on Advances in Computer Technology, Information Science and Communications

Conference

Conference4th International Conference on Advances in Computer Technology, Information Science and Communications, CTISC 2022
Country/TerritoryChina
CitySuzhou
Period22/04/2224/04/22

Keywords

  • CNN
  • Gammatone Frequency Cepstral Coefficient (GFCC)
  • Mel Frequency Cepstrum Coefficient (MFCC)
  • Underwater communication

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