拓展TOPSIS的地面目标关联算法

地面战场复杂的背景环境和目标的强机动性,使得传统关联方法所必需的先验信息不易获得,且传统关联方法仅利用状态信息进行关联,导致关联信息量不足,从而关联正确率不高。针对上述问题,采用无需任何先验假设的TOPS IS,在状态信息的基础上引入属性信息,作为拓展TOPS IS的评价指标,利用熵权确定各指标权重,最后用相对贴近度确定关联排序。仿真结果表明,该算法有效地提高了关联正确率,且能够满足实时性要求。

Ground Target Association Algorithm Based on Extensive TOPSIS

Prior information of ground targets were obtained difficultly because of complex background environment and strong mobility of targets.Association accuracy was low because association information was inadequate only with state information in the traditional method.Aiming at above problems,this paper firstly adopted TOPSIS without any prior assumptions,took attribute information as the evaluation index of extensive TOPSIS,then the index weights are determined by the entropy weight,finally decides the association order by means of relative approach degree.The Simulation result shows that the algorithm improves association accuracy effectively and meets the real-time need.