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研究了大气层外拦截多目标分配策略。基于目标威胁度和拦截有效程度建立目标分配模型,设计了一种基于粒子群算法的目标分配策略,针对算法存在的缺陷,利用遗传算法交叉思想对粒子更新策略进行了改进,并对其性能进行了数值仿真分析。结果表明,改进的算法能有效克服基本粒子群算法的弱点,具有收敛性快、稳定性好的特点,没有出现优化退化现象且对不同拦截场景具有较强适应能力。
A multi-objective allocation strategy for intercept in the atmosphere is studied. A target allocation model based on particle swarm optimization (PSO) is proposed based on the target threat degree and the interception effectiveness. Aiming at the defects of the algorithm, the particle updating strategy is improved by the idea of crossover and the performance of the particle updating is improved Numerical simulation analysis. The results show that the improved algorithm can effectively overcome the weaknesses of the basic particle swarm optimization algorithm, and has the characteristics of fast convergence and good stability. The optimized degeneracy does not occur and has strong adaptability to different interception scenarios.