Feature extraction method of ship-radiated noise based on dispersion entropy: A review

There is abundant ship information in ship-radiated noise, which is helpful for ship target recognition, classification and tracking. However, owing to the increasing complexity of the marine environment, it makes difficult to extract S-RN features. Dispersion entropy has been proven to be an excell...

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Main Author: Guanni Ji
Format: Article
Language:English
Published: Frontiers Media S.A. 2023-02-01
Series:Frontiers in Physics
Subjects:
Online Access:https://www.frontiersin.org/articles/10.3389/fphy.2023.1146493/full
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author Guanni Ji
author_facet Guanni Ji
author_sort Guanni Ji
collection DOAJ
description There is abundant ship information in ship-radiated noise, which is helpful for ship target recognition, classification and tracking. However, owing to the increasing complexity of the marine environment, it makes difficult to extract S-RN features. Dispersion entropy has been proven to be an excellent method to extract the features of S-RN by analyzing the complexity of S-RN, and has been widely used in feature extraction of S-RN. This paper summarizes the research progress of DE in the feature extraction of S-RN in recent years, and provides a comprehensive reference for researchers related to this topic. First, DE and its improved algorithm are described. Then the traditional and DE-based S-RN feature extraction methods are summarized, and the application of DE in S-RN feature extraction methods is concluded from two aspects: methods that apply DE algorithms only and methods that combine DE with mode decomposition algorithms. Finally, the research prospects of DE and the summary of this paper are given.
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spelling doaj.art-57451b19550f428abcf4c6a29a71b0f72023-02-21T06:17:24ZengFrontiers Media S.A.Frontiers in Physics2296-424X2023-02-011110.3389/fphy.2023.11464931146493Feature extraction method of ship-radiated noise based on dispersion entropy: A reviewGuanni JiThere is abundant ship information in ship-radiated noise, which is helpful for ship target recognition, classification and tracking. However, owing to the increasing complexity of the marine environment, it makes difficult to extract S-RN features. Dispersion entropy has been proven to be an excellent method to extract the features of S-RN by analyzing the complexity of S-RN, and has been widely used in feature extraction of S-RN. This paper summarizes the research progress of DE in the feature extraction of S-RN in recent years, and provides a comprehensive reference for researchers related to this topic. First, DE and its improved algorithm are described. Then the traditional and DE-based S-RN feature extraction methods are summarized, and the application of DE in S-RN feature extraction methods is concluded from two aspects: methods that apply DE algorithms only and methods that combine DE with mode decomposition algorithms. Finally, the research prospects of DE and the summary of this paper are given.https://www.frontiersin.org/articles/10.3389/fphy.2023.1146493/fullship-radiated noisefeature extractiondispersion entropymode decompositionentropy
spellingShingle Guanni Ji
Feature extraction method of ship-radiated noise based on dispersion entropy: A review
Frontiers in Physics
ship-radiated noise
feature extraction
dispersion entropy
mode decomposition
entropy
title Feature extraction method of ship-radiated noise based on dispersion entropy: A review
title_full Feature extraction method of ship-radiated noise based on dispersion entropy: A review
title_fullStr Feature extraction method of ship-radiated noise based on dispersion entropy: A review
title_full_unstemmed Feature extraction method of ship-radiated noise based on dispersion entropy: A review
title_short Feature extraction method of ship-radiated noise based on dispersion entropy: A review
title_sort feature extraction method of ship radiated noise based on dispersion entropy a review
topic ship-radiated noise
feature extraction
dispersion entropy
mode decomposition
entropy
url https://www.frontiersin.org/articles/10.3389/fphy.2023.1146493/full
work_keys_str_mv AT guanniji featureextractionmethodofshipradiatednoisebasedondispersionentropyareview