基于匹配空间变换的群目标信号分离与重构

Group-target Signal Separation and Reconstruction Based on Matched Space Transform

针对窄带雷达获取的弹道中段群目标回波错综交叠、难以分离的问题,提出了一种基于匹配空间变换的群目标微多普勒特征提取方法。在构建群目标模型的基础上,利用自相关法提取出各子目标的微动周期,并结合微多普勒曲线变化规律,构造出对应的匹配空间。最后利用能量峰值搜索法结合CLEAN算法,依次估计出该子目标各散射点参数,并重构出回波信号。仿真结果表明,该方法能够克服背景噪声和信号混叠的影响,较好的实现了中段群目标的分辨。

In view of the problem of intricate overlap and difficult separation in midcourse group-target echo by narrowband radar, a novel algorithm based on matched space transform was proposed to extract its micro-Doppler features. On the basis of modeling of group-target, period of each sub-target was obtained using autocorrelation method first. Then with the characteristic of micro-Doppler curve along time variable, the corresponding matched space was structured. Finally, the parameters of each scattering point were estimated utilizing energy peak searching and CLEAN algorithm. Thus the echo was reconstructed. Simulation results indicate that the proposed method can achieve favorable identification despite of background noise and signal aliasing.