Research on ground-moving target type recognition based on local mean decomposition (LMD) and support vector machine (SVM)

Weibo Liu; Xiaojing Yu; Jiangtao Wen; Jinge Zhao; Kaiyan Li; Longjiang Zheng

doi:10.1117/12.2203650

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3 December 2015 Research on ground-moving target type recognition based on local mean decomposition (LMD) and support vector machine (SVM)

Weibo Liu, Xiaojing Yu, Jiangtao Wen, Jinge Zhao, Kaiyan Li, Longjiang Zheng

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Proceedings Volume 9794, Sixth International Conference on Electronics and Information Engineering; 979415 (2015) https://doi.org/10.1117/12.2203650
Event: Sixth International Conference on Electronics and Information Engineering, 2015, Dalian, China

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%.

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Weibo Liu, Xiaojing Yu, Jiangtao Wen, Jinge Zhao, Kaiyan Li, and Longjiang Zheng "Research on ground-moving target type recognition based on local mean decomposition (LMD) and support vector machine (SVM)", Proc. SPIE 9794, Sixth International Conference on Electronics and Information Engineering, 979415 (3 December 2015); https://doi.org/10.1117/12.2203650

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