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

被引：0

作者：

Liu, Weibo ^{[1
]}

Yu, Xiaojing ^{[2
]}

Wen, Jiangtao ^{[2
]}

Zhao, Jinge ^{[2
]}

Li, Kaiyan ^{[2
]}

Zheng, Longjiang ^{[2
]}

机构：

[1] Yanshan Univ, Phys Educ Coll, Qinhuangdao 066004, Peoples R China

[2] Yanshan Univ, Key Lab Measurement Technol & Instrumentat Hebei, Qinhuangdao 066004, Peoples R China

来源：

SIXTH INTERNATIONAL CONFERENCE ON ELECTRONICS AND INFORMATION ENGINEERING | 2015年 / 9794卷

关键词：

Local Mean Decomposition (LMD); Support Vector Machine (SVM); Ground-moving Target Type Recognition; Seismic Signal;

D O I：

10.1117/12.2203650

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

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%.

引用

页数：5