NDLI: The Underwater Acoustic Target Recognition Algorithm Based on Evidence Clustering

Content Provider	EDP Sciences
Author	Yang Zhang Jianhua Yang Hong Hou
Abstract	In underwater acoustic target recognition, the target signal is usually complex and the samples which are difficult to obtain also have some uncertain information. In order to effectively solve these problems, the evidence clustering recognition algorithm (TECRA) is presented. In this new method, the k-nearest neighbor are first determined by using the feature distance between the object and its neighbors in each class of the training set, and a reasonable initial basic belief assignments (bba's) for each target data are constructed by the improved k-nearest neighbor classification algorithm. Then the final global bba's of the target is obtained by optimizing the objective function of the algorithm. Finally the object can be recognized by the fusion result and the classification rule presented in the paper. Several experiments based on real underwater acoustic data sets are made to test the effectiveness of TECRA in comparison with some other methods. The results indicate that TECRA can effectively improve the recognition accuracy.
Ending Page	102
Starting Page	96
Page Count	7
File Format	HTM / HTML PDF
ISSN	10002758
Issue Number	1
Journal	Xibei Gongye Daxue Xuebao/Journal of Northwestern Polytechnical University
Volume Number	36
DOI	10.1051/jnwpu/20183610096
Alternate Webpage(s)	https://articles/jnwpu/abs/2018/01/jnwpu2018361p96/jnwpu2018361p96.html
Language	English
Publisher	The Northwestern Polytechnical University
Publisher Date	2018-02-01
Access Restriction	Open
Rights Holder	© 2018 Journal of Northwestern Polytechnical University. All rights reserved.
Subject Keyword	clustering algorithm computational efficiency evidence k-nearest neighbor support vector machines pattern recognition clustering algorithm / computational efficiency / evidence k-nearest neighbor / support vector machines / pattern recognition
Content Type	Text
Resource Type	Article
Subject	Engineering

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