基于质心参照拓扑的灰色航迹抗差关联算法

Grey track anti-bias association algorithm based on centroid topology of reference

针对传感器系统误差影响下利用目标拓扑信息的航迹关联算法性能受参照目标状态估计精度制约的问题,提出了一种基于质心参照拓扑的灰色航迹抗差关联算法。该算法以传感器共同观测目标的融合质心位置和航向为参照,建立目标拓扑描述向量,然后采用序贯修正的灰色关联分析方法计算各传感器航迹间的灰关联度,最后以灰关联度为检验统计量进行全局最优的航迹抗差关联判决。仿真结果表明,在随机交叉目标和密集平行编队环境下,该算法的性能和稳健性明显优于传统方法。

The performance of tracking association algorithm using target topology information is influenced by the estimation accuracy of the reference target state because of sensor bias. To solve such problem, a grey track anti-bias association algorithm based on centroid topology of reference is proposed. First, the algorithm takes the position and course of the sensor commonly observed targets ＇ fusion centroid as the reference, and constructs the target topological vector. Then, the subsequential modified grey association analysi,~ algorithm is used to calculate the grey association degree of the sensors. Finally, the global optimal track anti-bias association is carried out using the grey association degree as test statistical vector. Simulation results show that the performance and robustness of the proposed algorithm are better than the traditional algorithm apparently in random cross targets and dense parallel formation environment.