针对地面防空**系统中多传感器分配问题, 首先研究基于Cramér-Rao下限的多传感器跟踪分配模型, 根据目标跟踪过程的特点将Cramér-Rao下限引入分配模型, 使得在进行跟踪分配时无需考虑目标跟踪滤波算法的选择, 同时通过细化约束条件使模型更加贴近实际作战情况。利用离散粒子群优化算法求解模型, 通过改进其搜索策略以及惯性权值和加权因子提高算法准确性与时效性, 给出了模型的求解步骤。关联仿真结果表明该分配方法的可行性, 并通过对比算法求解模型验证了改进DPSO算法的快速准确性。

A method is proposed based on Cramér-Rao Low Bound for multi-sensor assignment of land-based air defense weapon systems.The Cramér-Rao low bound is introduced into the multi-sensor assignment model according to the characteristics of tracking.Therefore it needs not to choose target tracking algorithm during assignment and the model is made more close to actual situation by detailing the constraints.Then the Discrete Particle Swarm Optimization (DPSO) algorithm is used for calculation.The searching strategy the inertia weight and learning factor are improved to increase the accuracy and timeliness.Finally the application example is given and the results show the feasibility of this method and the validity of the improved DPSO algorithm.