Blind Source Separation of Adjacent Group Targets Based on Coupling Scattering Center Removal

X. Sun, R. Wen, J. W. Lu, S. X. Sun, Z. He, D. Ding
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Abstract

Blind source separation (BSS) is an effective method to deal with the aliasing echo received by radar in the field of target detection. Single-channel BSS is a morbid problem of multi-channel BSS, but it has higher research value since it is more in line with practical application scenarios. Therefore, a single-channel BSS problem for adjacent group targets is studied in this paper. The coupling signals will be generated between targets when the distance between group targets is less than 10 times wavelength. It is difficult to accurately separate the source echoes of each target from the mixed echoes because the coupling echoes will have a certain influence on the mixed echoes of group targets. A new BSS method based on density clustering algorithm is proposed in this paper in order to solve this problem. Firstly, the strong scattering center points of group targets are obtained by radar imaging. Then, the strong scattering center points are clustered by the density-based clustering algorithm (DBCA). Next, the coupling echo is determined according to the variation of amplitude with azimuth, and the coupling signal is removed by the position information of the cluster. Finally, the mixed echo is separated, and the different separation methods are selected according to the spectrum of the mixed echo. 2-D imaging inverse operation is adopted if there is a single spectral peak; the empirical mode decomposition-fast independent component analysis (EMD-FastICA) algorithm is adopted if there are multiple spectral peaks. The simulation results show that this method can effectively separate the source signal from the echo containing coupling information within the error range.
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基于耦合散射中心去除的邻群目标盲源分离
在目标探测领域,盲源分离是处理雷达接收混叠回波的一种有效方法。单通道BSS是多通道BSS的病态问题,但更符合实际应用场景,具有更高的研究价值。因此,本文研究了相邻群目标的单通道BSS问题。当目标群之间的距离小于10倍波长时,目标之间会产生耦合信号。由于耦合回波会对群目标的混合回波产生一定的影响,因此很难准确地从混合回波中分离出每个目标的源回波。为了解决这一问题,本文提出了一种基于密度聚类算法的BSS方法。首先,通过雷达成像获取群目标的强散射中心点;然后,采用基于密度的聚类算法(DBCA)对强散射中心点进行聚类。然后根据振幅随方位角的变化确定耦合回波,利用聚类的位置信息去除耦合信号。最后,对混合回波进行分离,并根据混合回波的频谱选择不同的分离方法。单峰时采用二维成像逆操作;如果存在多个谱峰,则采用经验模式分解-快速独立分量分析(EMD-FastICA)算法。仿真结果表明,该方法能有效地将源信号从误差范围内含有耦合信息的回波中分离出来。
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