Research on Simulation of Multi-target Micro-Doppler Separation and Extraction in Ballistic Midcourse

doi:10.16182/j.issn1004731x.joss.201706006

Abstract

Abstract: Aiming at the intricate overlap and difficult separation and extraction of micro-Doppler information in Doppler spectra of warheads and fragments in midcourse, a novel method based on CEEMD and improved self-adaptive Viterbi algorithm was proposed. By analyzing the differences of micro-Doppler distribution between warheads and fragments, the echo was decomposed by CEEMD and each IMF was denoised by wavelet threshold denoising method, resulting in separation of warheads and fragments echo. The fragments signal was stretched, the optimal path was extracted combined with improved self-adaptive Viterbi algorithm, and the separation of multi-target signal and extraction of micro-Doppler was realized. Simulation validates that the proposed method can overcome the interference among multi-target and noise, which can achieve multi-target signal separation and micro-Doppler extraction well.

Key words: micro-Doppler, CEEMD, multi-target, Viterbi algorithm, feature extraction

CLC Number:

TN95

Wang Yizhe, Feng Cunqian, Li Jingqing. Research on Simulation of Multi-target Micro-Doppler Separation and Extraction in Ballistic Midcourse[J]. Journal of System Simulation, 2017, 29(6): 1201-1209.

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