Analysis of micro-Doppler signatures of vibration targets using EMD and SPWVD

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• 作者：Yan Wang¹ ; ^aAuthor Vitae ; Xi Wu^b ; ¹Author Vitae ; Wenzao Li^a ; ^bAuthor Vitae ; Zhi Li^aAuthor Vitae ; Yi Zhang^a ; Author Vitae ; Jiliu Zhou^aAuthor Vitae
• 关键词：Micro-Doppler ; Vibration target ; Smoothed Pseudo Wigner-Ville Distribution (SPWVD) ; Empirical Mode Decomposition (EMD) ; Ensemble Empirical Mode Decomposition (EEMD)
• 刊名：Neurocomputing
• 出版年：2016
• 出版时间：1 January 2016
• 年：2016
• 卷：171
• 期：Complete
• 页码：48-56
• 全文大小：6184 K

文摘

In the micro-Doppler signature analysis of vibration targets, the joint time–frequency methods can provide useful information for target detection, classification, and recognition. In this paper, we proposed a procedure which combines both Empirical Mode Decomposition (EMD) and Smoothed Pseudo Wigner-Ville Distribution (SPWVD) techniques for the micro-Doppler analysis. The Ensemble Empirical Mode Decomposition (EEMD) based method was also proposed to address the problem of mode mixing which may occur in EMD procedure. The simulation results showed that, compared with the traditional Cohen׳s class time–frequency method (SPWVD), the method we proposed achieved much better performance under three different conditions (severe noise, weak modulation and compound vibrations).