TY - JOUR
T1 - Micro-Doppler character analysis of moving objects using through-wall radar based on improved EEMD
AU - Wang, Hong
AU - Narayanan, Ram Mohan
AU - Zhou, Zheng Ou
AU - Li, Ting Jun
AU - Kong, Ling Jiang
PY - 2010/6
Y1 - 2010/6
N2 - The micro-Doppler signals of human's heartbeat breathe and arm-moving using through-wall radar is 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.
AB - The micro-Doppler signals of human's heartbeat breathe and arm-moving using through-wall radar is 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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U2 - 10.3724/SP.J.1146.2009.00899
DO - 10.3724/SP.J.1146.2009.00899
M3 - Article
AN - SCOPUS:77954360937
SN - 1009-5896
VL - 32
SP - 1355
EP - 1360
JO - Dianzi Yu Xinxi Xuebao/Journal of Electronics and Information Technology
JF - Dianzi Yu Xinxi Xuebao/Journal of Electronics and Information Technology
IS - 6
ER -