一种用于空间群目标分辨的滑动窗轨迹跟踪算法

针对大多数现有的微多普勒分析理论难以解决空间群目标的监测与识别问题，本文提出一种基于提取目标运动特征的弹道中段群目标分辨方法。首先建立了多个具有滑动散射中心的旋转对称目标模型并得到其m-D曲线，在此基础上，利用形态学图像处理方法抑制一维距离像旁瓣，然后提出了一种滑动窗轨迹跟踪的方法分离出各散射点相互交叉的m-D曲线，再对分离结果进行经验模式分解(Empirical-Mode Decomposition, EMD)，最后通过提取能够反映目标运动特征的固有模态函数(Intrinsic Mode Function ,IMF)，实现了群目标分辨。仿真实验校验了所提方法的可行性和鲁棒性。

A Sliding Window Tracking Algorithm for Distinguishing Space Group Targets

To solve the problem that most of the existing micro-Doppler analysis theories are hard to be utilized in monitoring and distinguishing space group targets, an algorithm for distinguishing ballistic midcourse group targets based on motion feature extraction is proposed. On the basis of building multiple rotationally symmetric target models with sliding-type scattering centers and obtaining m-D curves, an algorithm in morphology image processing is firstly utilized to suppress the lobes of range profile, and then an algorithm for tracking the trace of sliding window is put forward to separate the cross m-D curves. Then the Empirical-Mode Decomposition(EMD) method is utilized to extract IMF information for reflecting of the targets’ features. In this way, distinguishing of group targets is achieved.Computer simulation is used to illuminate both feasibility and robustness of this algorithm.