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《Journal of Academy of Armored Force Engineering》 2014-04
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Extraction of Micro-Doppler Features of Vehicle by Joint EEMD and AOK-TFR

ZHANG Wan-jun;NIU Min-jie;WU Xiao-ying;Department of Arms Engineering,Academy of Armored Force Engineering;  
By using the continuous wave radar to detect moving vehicle,it is difficult to extract and analyze nonlinear and nonstationary multi-component echo signals. So,the method of joint Ensemble Empirical Mode Decomposition( EEMD) and Adaptive Optimal Kernel Time-Frequency Distribution( AOKTFR) is presented to extract micro-Doppler features of moving vehicle. Firstly,the echo signal mathematical model of composite modulation effect from vehicle body vibration and rotation of the wheel is established,the multi-component echo signal is decomposed by EEMD. Then a clear micro-Doppler timefrequency image is obtained through analyzing the intrinsic mode component of echo signal by joint AOKTFR,and mode mixing caused by ground clutters is effectively overcome. The simulation results show that the micro-Doppler feature parameters extracted by this method agree well with simulation parameters and the effectiveness of the method is validated.
【CateGory Index】: TN957.51
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