点迹-曲线关联算法的旋转对称群目标分辨

基于微多普勒效应分析的弹道目标识别得到了广泛研究,然而传统的微多普勒特征提取技术大都难以解决空间群目标的分辨与识别。针对这一问题,提出了一种基于点迹-曲线关联算法的空间群目标分辨方法。在以旋转对称群目标为研究对象的前提下,建立了具有滑动散射特性的目标模型并分析推导了散射点的微动表达式,利用点迹凝聚处理抑制了一维距离像旁瓣,在此基础上,提出了点迹-曲线关联算法分离出混叠的群目标微多普勒曲线,通过各曲线的极值包络特性差异实现了旋转对称群目标分辨。实验仿真验证了本方法的正确性和可行性。

Distinguishing of Rotationally Symmetric Group Targets Based on Plot-curve Association Algorithm

To solve the problem that the traditional micro-Doppler analysis theories are hard to be utilized in monitoring and recognition of space group targets, an algorithm for distinguishing of space group targets based on plot-curve association is proposed. Taking the rotationally symmetric group targets into consideration, the target model which has sliding-type scattering centers is built firstly. Then, on the basis of suppressing the side-lobes of rang profile by plot condensation, an algorithm based on plot-curve association is put forward to separate the cross m-D curves. Finally, the differences of extreme value envelopes of curves can be used to distinguish rotationally symmetric group targets. The computer simulation and the simulation result illuminate and verify the correctness and validity of this algorithm.