弹道中段微多普勒分离与提取仿真研究

发布时间：2018-03-07 06:40

  本文选题：微多普勒　切入点：完备总体经验模态分解　出处：《系统仿真学报》2017年06期 　论文类型：期刊论文

【摘要】：针对弹道中段弹头和碎片的微多普勒信息在多普勒谱中交缠重叠、难以分离与提取的问题,提出了一种基于完备总体经验模态分解(CEEMD)和改进自适应Viterbi算法相结合的多目标微多普勒信号分离与提取方法。通过分析进动弹头与旋转碎片微多普勒分布的差异性,对多目标回波信号进行CEEMD分解,结合小波阈值去噪方法,对各本征模态函数(IMF)进行分层处理并累加,分离出了弹头和碎片回波。对碎片信号进行了扩展处理,利用改进自适应Viterbi算法,抽取出相应的最优路径,实现多目标信号分离与微多普勒提取。仿真表明,该方法能有效克服多目标之间的干扰及噪声的影响,较好地实现了弹道多目标分离及微多普勒提取。
[Abstract]:Aiming at the problem that the microDoppler information of warhead and debris in the middle part of trajectory overlaps in Doppler spectrum, it is difficult to separate and extract. A multi-target microDoppler signal separation and extraction method based on complete global empirical mode decomposition (EMD) and improved adaptive Viterbi algorithm is proposed. The multi-target echo signal is decomposed by CEEMD, combined with wavelet threshold denoising method, each intrinsic mode function (IMF) is delaminated and accumulated, the warhead and fragment echo are separated, and the fragment signal is extended. The improved adaptive Viterbi algorithm is used to extract the corresponding optimal path to realize multi-target signal separation and micro-Doppler extraction. The simulation results show that the proposed method can effectively overcome the influence of interference and noise between multiple targets. Ballistic multi-target separation and micro-Doppler extraction are well realized.
【作者单位】： 空军工程大学防空反导学院;
【基金】：国家自然科学基金(61372166,61501495) 陕西省自然科学基础研究计划(2014JM8308)
【分类号】：TJ761.3;TN957.51
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本文编号：1578366