系统误差下基于双重模糊拓扑的编队航迹精细关联算法

为解决系统误差下编队内各目标航迹精细关联的难题，基于编队目标航迹的特点，利用模糊拓扑的思想，提出了一种系统误差下基于双重模糊拓扑的编队航迹精细关联算法.算法首先基于循环阈值模型对各传感器获得的航迹进行编队识别，然后利用编队中心航迹代替编队整体，深入分析系统误差对编队中心航迹的影响，建立第一重模糊拓扑模型，完成编队航迹的预互联和普通目标航迹的对准关联，最后基于预关联编队内目标航迹之间或与航迹关联对之间的拓扑关系建立第二重模糊拓扑模型，实现编队内目标航迹的精细关联.经仿真数据验证，与基于目标不变信息量的模糊航迹对准关联算法、基于航迹迭代的航迹对准关联算法和修正的加权法相比，该算法综合性能明显优越，能很好满足工程上对系统误差下编队内目标航迹精细关联的需求. 

Formation Targets Track Refined Correlation Algorithm with Systematic Error Based on Double Fussy Topology

Aiming to solve the track refined correlation problem of the formation targets with systematic errors, based on the characteristics of the formation tracks and fussy topology theory, an algorithm of track refined correlation within formation targets based on double fussy topology was proposed considering systematic errors. In this algorithm, the formation identification of each sensor was obtained based on the cyclic threshold model firstly. And then the formation center was used to replace the whole formation, the first fussy topology model was established by deeply analyzing the effect of system error on the track of formation center, that is to say the pre-interconnection of formation tracks and alignment of common target tracks were completed. At last, the second fussy topology model was established by the topological relations between the pre-interconnection of formation tracks and correlated tracks, in order to realize formation targets track refined correlation. The analysis results of the simulation data show that the general performance of this algorithm, which can meet the engineering requirement of the track refined correlation of the group targets with systematic errors very well, is better than that of fuzzy track alignment-correlation algorithm based on target invariant information, track alignment-correlation algorithm based on iterative closest track and modified weighted track correlation algorithm.