A Group Target Track Correlation Algorithm Based on Systematic Error Estimation

Aiming to solve the track refined correlation problem of the group targets with systematic errors, based on the characteristics of the group tracks,an algorithm of track refined correlationwithingroup targets based on systematic error compensation is proposed with the error estimation technique and the track correlation technique. In this algorithm, the groups areidentifiedwith the tracks of the sensors based on the circulatory threshold model firstly. Secondly, the preparatory correlation groups with the nearest resolving state are searched or established based on group track state identification model. Thirdly, the final systematic errors are estimated with group track systematic error estimation model and error validation model. What is more, the error compensation is completed. Finally, group track refined correlation is done with the traditional track correlation algorithms. 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 topological information, track alignment-correlation algorithm based on iterative closest track and modified weighted track correlation algorithm.