多约束条件下多目标反导最优分配策略研究

Optimal Appointment for Multiple Targets Interception with Multi-Constraints

针对弹道导弹中段拦截问题,研究了多对多场景下的武器-目标最优分配策略。首先,提出了一种拦截弹发射诸元和拦截诸元快速解算方法,并建立了最优分配指标模型,实现了拦截效能和威胁指标的快速求解。由于能够预判弹-目末交战过程,较传统的基于单发拦截概率的方法而言,提出的方法在拦截效能的计算上更具实际意义。其次,提出了一种改进粒子群优化算法,以及一种基于种群平均适应度方差的动态变异策略,通过量化群体进化过程的方式从根本上提升了算法的搜索效率,保证了最优分配策略的快速生成。最后通过仿真计算验证了方法的准确性和可行性。

The optimal weapon-target appointment in the scenario of multiple interceptors and missiles,which is widely concerned in the midcourse interception of ballistic missiles,is researched in this paper.First,a fast computation method is proposed to calculate the launch and interception date of the interceptor;then the optimization model of the optimal weapon-target appointment is developed.In this way,the threat and interception performance indexes can be quickly derived.In addition,because of the prediction of the process of final engagement,the proposed method can better represent the interception performance in comparison with traditional methods that depend on interception probability.Second,an improved particle swarm optimization method(PSO)is proposed.By proposing a turbulence strategy based on the variance of a swarm-fitness-function.In this way,the evolution process is quantified and the searching efficiency of PSO is dramatically improved to quickly generate the optimal results of appointment.Finally,numerical simulation is provided to validity the effectiveness of the proposed method.