一种基于系统误差自动补偿的编队目标航迹精细关联算法

为解决编队内各目标航迹精细关联的难题，按照编队目标航迹的特点，结合误差估计技术及航迹关联技术，提出了一种基于系统误差自动补偿的编队目标航迹精细关联算法，该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，并按编队中心航迹完成编队航迹的整体预关联，然后基于编队航迹状态识别模型，搜索或建立分辩状态最接近的预关联编队航迹，并基于编队航迹系统误差估计模型和误差确认模型，获得最终的系统误差估计值，自动完成系统误差补偿，最后利用传统的航迹关联算法进行编队航迹的精细关联。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和基于航迹迭代的航迹对准关联算法相比，该算法具有耗时少、关联性能有效稳定等综合优势，能较好的满足工程上对系统误差下编队内目标航迹的精确关联需求。

An Algorithm of Track Refined Correlation within Formation Targets Based on Systematic Error Automatic Compensation

Aiming to solve the track refined correlation problem of the formation targets with systematic errors, an algorithm of track refined correlation for formation targets based on systematic error automatic compensation and the characteristics of the formation tracks was proposed with the error estimation technique and the track correlation technique. In this algorithm, the formations are identified by the tracks of the sensors based on the circulatory threshold model firstly. Secondly, the preparatory correlation formations with the nearest resolving state are searched or established based on the formation track state identification model. Thirdly, the final systematic errors are estimated with formation track systematic error estimation model and error validation model. Furthermore, the error compensation is completed. Finally, formation track refined correlation is done by use of the traditional track correlation algorithms. The analysis results of the simulation data show that the general performance of this algorithm can meet the engineering requirement of the track refined correlation for the formation targets very well. It is much better than that of fuzzy track alignment-correlation algorithm based on target topological information, track alignment-correlation algorithm based on iterative closest track and modified weighted track correlation algorithm.