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Proceedings Paper

Research on ground-moving target type recognition based on local mean decomposition (LMD) and support vector machine (SVM)
Author(s): Weibo Liu; Xiaojing Yu; Jiangtao Wen; Jinge Zhao; Kaiyan Li; Longjiang Zheng
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Paper Abstract

This paper presents a target type recognition method based on local mean decomposition (LMD) and support vector machine (SVM) using the seismic signal caused by the ground-moving target. The wavelet packet filter is used for improving signal noise ratio (SNR). Then, the seismic signal is decomposed into several production function (PF) components. The feature vector is composed of the energy of each principal PF. SVM is used as classifier which discriminate the human, car and truck. The experiment result shows that, the average discrimination accuracy of proposed method is over 92.0%.

Paper Details

Date Published: 3 December 2015
PDF: 5 pages
Proc. SPIE 9794, Sixth International Conference on Electronics and Information Engineering, 979415 (3 December 2015); doi: 10.1117/12.2203650
Show Author Affiliations
Weibo Liu, Yanshan Univ. (China)
Xiaojing Yu, Yanshan Univ. (China)
Jiangtao Wen, Yanshan Univ. (China)
Jinge Zhao, Yanshan Univ. (China)
Kaiyan Li, Yanshan Univ. (China)
Longjiang Zheng, Yanshan Univ. (China)


Published in SPIE Proceedings Vol. 9794:
Sixth International Conference on Electronics and Information Engineering
Qiang Zhang, Editor(s)

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