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| Micro-Doppler Character Analysis of Moving Objects Using Through-Wall Radar Based on Improved EEMD |
| Wang Hong①; Narayanan R M②; Zhou Zheng-ou①; Li Ting-jun①; Kong Ling-jiang① |
| ①College of Electronic Engineering, University of Electronic Science and Technology of China, Chengdu 610054, China; ②Department of Electrical Engineering, Pennsylvania State University, University Park, PA 16802, USA |
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Abstract The micro-Doppler signals of human’s heartbeat, breathe and arm-moving using through-wall radar are nonlinear and non-stationary, which can be analyzed by Empirical Mode Decomposition (EMD). Due to the mode mixing problem in EMD, an improved Ensemble Empirical Mode Decomposition (EEMD) is proposed in this paper, and is applied to the human micro-Doppler character analysis of the through-wall radar. The time-frequency-energy spectrum is obtained by using Hilbert-Huang Transform (HHT) to every Intrinsic Mode Functions (IMF). The analysis on simulation data and experimental results show that the improved EEMD can effectively eliminate the mode mixing problem in EMD, which means different frequency scales in human’s micro-Doppler signals are decomposed in different IMF. Furthermore, this method can restrain the noise in the original signal and more detail information can be seen clearly in the time-frequency spectrum.
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Received: 19 June 2009
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Corresponding Authors:
Wang Hong
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2010, Vol. 32 
