Underwater Target Recognition Based on Line Spectrum and Support Vector Machine

DOI

10.2991/mce-14.2014.17How to use a DOI?

Keywords

line spectrum; feature extraction; Support vector machine; target recognition; algorithms

Abstract

To increase the classification of underwater target recognition by ship radiated noise signals, the feature extraction method of line spectrum and classification algorithm of support vector machine (SVM) are adopted in the paper. The basic principles of power spectrum and SVM are briefly introduced at first. Then the signals of ship radiated are processed by the power spectrum estimation and the nonlinear least-square polynomial to fitting the continuous spectrum. The ultimate line spectrum is obtained through selecting peak and removes side lobe, and then extracts the feature of number and intensity of line spectrum from it. At last, the characteristic vector is established with normalization process and the signals are classified by SVM with parameter optimization. The simulation experiment results demonstrate that the ship radiated signals can be classified or recognized availably based on line spectrum feature and SVM. This paper presents a method of underwater target recognition and provides guidance for the research on multi-classes recognition algorithms.

Copyright

© 2014, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Jian Liu
AU  - Yang He
AU  - Zhong Liu
AU  - Ying Xiong
PY  - 2014/03
DA  - 2014/03
TI  - Underwater Target Recognition Based on Line Spectrum and Support Vector Machine
BT  - Proceedings of the 2014 International Conference on Mechatronics, Control and Electronic Engineering
PB  - Atlantis Press
SP  - 79
EP  - 84
SN  - 1951-6851
UR  - https://doi.org/10.2991/mce-14.2014.17
DO  - 10.2991/mce-14.2014.17
ID  - Liu2014/03
ER  -