Active Sonar Target Classification Method Based on Fisher’s Dictionary Learning

The marine environment is complex and changeable, and the interference of noise and reverberation seriously affects the classification performance of active sonar equipment. In particular, when the targets to be measured have similar characteristics, underwater classification becomes more complex. T...

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Autores principales:	Tongjing Sun, Jiwei Jin, Tong Liu, Jun Zhang
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	active sonar target classification fisher criteria dictionary learning sparse representation classification Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999
Acceso en línea:	https://doaj.org/article/b08f97be6767416d91d765b2a7e7c085
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id	oai:doaj.org-article:b08f97be6767416d91d765b2a7e7c085
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spelling	oai:doaj.org-article:b08f97be6767416d91d765b2a7e7c0852021-11-25T16:33:42ZActive Sonar Target Classification Method Based on Fisher’s Dictionary Learning10.3390/app1122106352076-3417https://doaj.org/article/b08f97be6767416d91d765b2a7e7c0852021-11-01T00:00:00Zhttps://www.mdpi.com/2076-3417/11/22/10635https://doaj.org/toc/2076-3417The marine environment is complex and changeable, and the interference of noise and reverberation seriously affects the classification performance of active sonar equipment. In particular, when the targets to be measured have similar characteristics, underwater classification becomes more complex. Therefore, a strong, recognizable algorithm needs to be developed that can handle similar feature targets in a reverberation environment. This paper combines Fisher’s discriminant criterion and a dictionary-learning-based sparse representation classification algorithm, and proposes an active sonar target classification method based on Fisher discriminant dictionary learning (FDDL). Based on the learning dictionaries, the proposed method introduces the Fisher restriction criterion to limit the sparse coefficients, thereby obtaining a more discriminating dictionary; finally, it distinguishes the category according to the reconstruction errors of the reconstructed signal and the signal to be measured. The classification performance is compared with the existing methods, such as SVM (Support Vector Machine), SRC (Sparse Representation Based Classification), D-KSVD (Discriminative K-Singular Value Decomposition), and LC-KSVD (label-consistent K-SVD), and the experimental results show that FDDL has a better classification performance than the existing classification methods.Tongjing SunJiwei JinTong LiuJun ZhangMDPI AGarticleactive sonar target classificationfisher criteriadictionary learningsparse representation classificationTechnologyTEngineering (General). Civil engineering (General)TA1-2040Biology (General)QH301-705.5PhysicsQC1-999ChemistryQD1-999ENApplied Sciences, Vol 11, Iss 10635, p 10635 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	active sonar target classification fisher criteria dictionary learning sparse representation classification Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999
spellingShingle	active sonar target classification fisher criteria dictionary learning sparse representation classification Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999 Tongjing Sun Jiwei Jin Tong Liu Jun Zhang Active Sonar Target Classification Method Based on Fisher’s Dictionary Learning
description	The marine environment is complex and changeable, and the interference of noise and reverberation seriously affects the classification performance of active sonar equipment. In particular, when the targets to be measured have similar characteristics, underwater classification becomes more complex. Therefore, a strong, recognizable algorithm needs to be developed that can handle similar feature targets in a reverberation environment. This paper combines Fisher’s discriminant criterion and a dictionary-learning-based sparse representation classification algorithm, and proposes an active sonar target classification method based on Fisher discriminant dictionary learning (FDDL). Based on the learning dictionaries, the proposed method introduces the Fisher restriction criterion to limit the sparse coefficients, thereby obtaining a more discriminating dictionary; finally, it distinguishes the category according to the reconstruction errors of the reconstructed signal and the signal to be measured. The classification performance is compared with the existing methods, such as SVM (Support Vector Machine), SRC (Sparse Representation Based Classification), D-KSVD (Discriminative K-Singular Value Decomposition), and LC-KSVD (label-consistent K-SVD), and the experimental results show that FDDL has a better classification performance than the existing classification methods.
format	article
author	Tongjing Sun Jiwei Jin Tong Liu Jun Zhang
author_facet	Tongjing Sun Jiwei Jin Tong Liu Jun Zhang
author_sort	Tongjing Sun
title	Active Sonar Target Classification Method Based on Fisher’s Dictionary Learning
title_short	Active Sonar Target Classification Method Based on Fisher’s Dictionary Learning
title_full	Active Sonar Target Classification Method Based on Fisher’s Dictionary Learning
title_fullStr	Active Sonar Target Classification Method Based on Fisher’s Dictionary Learning
title_full_unstemmed	Active Sonar Target Classification Method Based on Fisher’s Dictionary Learning
title_sort	active sonar target classification method based on fisher’s dictionary learning
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/b08f97be6767416d91d765b2a7e7c085
work_keys_str_mv	AT tongjingsun activesonartargetclassificationmethodbasedonfishersdictionarylearning AT jiweijin activesonartargetclassificationmethodbasedonfishersdictionarylearning AT tongliu activesonartargetclassificationmethodbasedonfishersdictionarylearning AT junzhang activesonartargetclassificationmethodbasedonfishersdictionarylearning
_version_	1718413159869448192

Active Sonar Target Classification Method Based on Fisher’s Dictionary Learning

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