Study on the feature extraction and classification of underwater target radiated noise based on bispectrum

Yuan Peng; Lin Cao; Lin Mu; Fengzhen Zhang; Zhaohui Zhang

doi:10.1117/12.2203193

3 December 2015 Study on the feature extraction and classification of underwater target radiated noise based on bispectrum

Yuan Peng, Lin Cao, Lin Mu, Fengzhen Zhang, Zhaohui Zhang

Author Affiliations +

Proceedings Volume 9794, Sixth International Conference on Electronics and Information Engineering; 97941M (2015) https://doi.org/10.1117/12.2203193
Event: Sixth International Conference on Electronics and Information Engineering, 2015, Dalian, China

Abstract

The radiated noise of underwater targets apparently consists of non-Gaussian ingredients. In the paper, based on plenty of radiated noise data, non-Gaussian feature of target signals is studied via high-order cumulates. Then, from Bispectrum estimation and WALSH dimensionality reduction, 65 dimensional Bispectrum feature from different kind of targets is extracted. The results show that the approach can efficiently classify underwater targets, and the colored Gaussian noise is restrained. The ration of recognition can arrive 92% toward three different kinds of underwater targets.

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Yuan Peng, Lin Cao, Lin Mu, Fengzhen Zhang, and Zhaohui Zhang "Study on the feature extraction and classification of underwater target radiated noise based on bispectrum ", Proc. SPIE 9794, Sixth International Conference on Electronics and Information Engineering, 97941M (3 December 2015); https://doi.org/10.1117/12.2203193

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