Research On Weapon Target Assignment Based On Intelligent Algorithm

Weapon-target assignment(WTA)problem is the key to air defense command,aiming at seeking a proper assignment of targets to weapons and hence enhancing mission efficiencies.Known as an NP-complete problem,WTA problem involves variables as weapon performance and target threat.With the development and extensive military application of information weapons and equipment,WTA problem arouses wide concern from military industry.Based on the analysis of current research and common algorithms of WPA problem,this study classifies the WTA problem from the perspectives of combat modes,target threat and time factors,and emphasizes on the definitions and model buildings of static and dynamic WTA problems.This thesis analyses the static and dynamic WTA problems respectively based on intelligent algorithms on basis of current research.In order to avoid defects of convergence rate and convergence precision in current algorithms of static single-objective WTA problem,this thesis proposes an allocation scheme based on improved artificial fish swarm algorithm(AFSA).By employing particle swam optimization,the fish swarm vision is adaptively adjusted,in combination with genetic operator to avoid local optimum in the algorithm.The study simulates several algorithms according to actual combat scenes.With comparison and analysis,simulation results show that the proposed algorithm can improve convergence rate and convergence precision effectively.Aiming at the problem of objective function simplification in static WTA problem,a biobjective optimization model maximizing the expected damage of the enemy and minimizing the cost of missiles is designed.With the purpose of improving convergence rate and precision,this thesis further proposes the two-stage evolutionary strategy based on multi-objective AFSA,and improves the rules of swarm、follow in traditional algorithms to form new state update rules.The improved genetic operator is employed to update the obtained Pareto front solutions and population.Simulation results show that the improved multiobjective AFSA can be successfully used in solution to WTA,and Aiming at the insufficient consideration of target movements and multichannel weapons in current models in dynamic WTA problems,this study,based on the analysis of current research and common intelligent algorithms of dynamic WPA problem,proposes the models of weapon-target paired time window and multi-stage weapon-target assignment to further solve the problems of multichannel weapons transfer time and attacking targets in stages in dynamic combat situations.In order to realize the model’s simulation in actual combat scenes,this study proposes an improved ant colony algorithm,redefines the calculation of transfer probability and pheromone updating rules,and verifies the effects of the improved algorithm in real air combats.Simulation results validates the effectiveness of the improved algorithm in dynamic problems,which can present effective attack schemes in combats quickly.Aiming at the insufficient consideration of target movements and multichannel weapons in current models in dynamic WTA problems,this study,based on the analysis of current research and common intelligent algorithms of dynamic WPA problem,proposes the models of weapon-target matching time window and multi-stage weapon-target assignment to further solve the problems of multichannel weapons transfer time and attacking targets in stages in dynamic combat situations.In order to realize the model’s simulation in actual combat scenes,this study proposes an improved ant colony algorithm,redefines the calculation of transfer probability and pheromone updating rules,and verifies the effects of the improved algorithm in real air combats.Simulation results validates the feasibility of the improved algorithm in dynamic problems,which can present effective attack schemes in combats quickly.