基于相位相关的部分可辨编队精细起始算法

针对部分可辨条件下编队目标的精细起始难题,提出了一种基于相位相关的部分可辨编队精细起始算法。首先,采用基于坐标映射距离差分的快速群分割与基于编队中心点的预互联对雷达量测进行预处理;然后,利用图像匹配中相位相关特性,将相邻时刻编队结构进行补偿对准,解决了低目标发现概率情况下的编队结构对准问题;最后,采用增加虚拟量测并后验判决的方式,结合最近邻法做编队航迹精细互联,在填补航迹缺失、增加正确航迹的同时抑制虚假航迹的产生。经仿真验证,与修正的逻辑法、基于相对位置矢量的灰色编队精细起始算法相比,本文所提算法在提高航迹正确起始率、抑制虚假航迹方面性能优势显著,且对环境杂波与雷达精度具有较好的鲁棒性,对目标发现概率具有较好的适应性。

Refined track initiation algorithm for partly resolvable group targets based on phase correlation

To deal with the problem of refined initiation in partly resolvable condition,a refined track initiation algorithm based on phase correlation is proposed in this paper.The radar measurements are preprocessed by using fast group segmentation based on coordinate mapping distance difference and pre-association based on group center point.To solve the problem of group topology alignment in low target detection probability condition,the phase correlation characteristics in image matching are then used in compensation and alignment of topological structure between adjacent times.Combined with the nearest neighbor method,a method by using virtual measurement and posterior decision is proposed to associate the group track refinedly,which can fill the missing tracks,add more correct ones,and at the same time suppress the false ones.The simulation results show that compared with the modified logic method and refined gray track initiation algorithm,the algorithm proposed has better performance in correct track initiation rate and suppression of false track,being robust to environment clutter and radar accuracy and more adaptable to target discovery probability.