近程防御武器系统精度分配算法研究

Research on Precision Allocation Algorithm of Short-Range Defense Weapon System

近程反导武器系统精度指标分配是系统设计过程中的一个重要环节,为避免在武器系统设计中造成设备性能(或造价)的浪费,有必要对各组成分系统的精度做出最佳的要求和分配。对于复杂的、非线性的近程防御武器系统精度分配问题,提出了基于粒子群算法的一种新的混合算法。首先对标准粒子群算法速度更新公式进行修改,避免微粒群陷入局部最优;然后引入差分算法的变异操作,再与鲍威尔算法相结合,以改进的混合粒子群算法为系统精度分配的启发式搜索策略实现精度分配。最后用一个实例进行仿真分析,仿真结果表明改进算法具有更好的稳定性和鲁棒性,是求解近程防御武器系统精度分配方案的一种有效算法。

The precision index assignment of short range antimissile weapon system is an important part in the process of system design. In order to avoid the waste of equipment performance （ or cost） in the design of weapon system, it is necessary to make the best request and allocation to the precision of each subsystem. A new hybrid algorithm based on particle swarm optimization （PSO） is proposed to solve the problem of complex and nonlinear shortrange defense weapon system. Firstly, the velocity update formula of the standard particle swarm optimization algorithm was modified to avoid the particle swarm falling into local optimum. Then, the mutation operation of differential algorithm was introduced and combined with Powell algorithm. Next, the improved hybrid particle swarm optimization （PSO） algorithm was used to realize the precision distribution of the system. Finally, the simulation results show that the improved algorithm has better stability and robustness, and it is an effective algorithm to solve the short range defense weapon system.