基于嵌套PSO算法的反无人机集群防空部署模型  

A Model for Air Defense Deployment Against UAV Swarm Based on Nested PSO Algorithm

作　　者：钟伟杰 李小兵[1] 常昊天 梁飞 ZHONG Weijie;LI Xiaobing;CHANG Haotian;LIANG Fei(Air Force Engineering University,Xi'an 710000,China)

机构地区：[1]空军工程大学,西安710000

出　　处：《电光与控制》2021年第12期6-10,16,共6页Electronics Optics & Control

基　　金：国家自然科学基金(61703424)。

摘　　要：无人机集群作战已逐渐成为未来空战的一种主流作战模式,给防空作战带来了严峻的威胁与挑战,先期合理部署防空武器直接影响着反无人机集群作战的总体效能。从防空作战敌我双方的角度综合分析了无人机集群的自主智能性与影响防空部署的主要因素,并将无人机集群与防空武器的博弈过程量化表示,提出了一种基于嵌套粒子群优化算法的防空部署模型。经仿真算例验证,以无人机集群威胁指数为指标所建模型可用于防空武器的优化部署,对反无人机集群作战决策问题研究有较高参考价值。UAV swarm operations are gradually becoming a mainstream mode of air combat in the futurewhich poses severe threats and challenges to air defense operations.The reasonable deployment of air defense weapons in advance has a direct impact on the overall performance of operations against UAV swarm.From the perspective of the two sides in air defense operationsthis paper comprehensively analyzes the autonomous intelligence of UAV swarm and the main factors affecting air defense deployment.Besidesthe confrontation process between UAV swarm and air defense weapons is quantifiedand an air defense deployment model based on nested Particle Swarm Optimization(PSO)algorithm is proposed.The simulation example verifies that the model taking the UAV swarm threat index as indicators can be used for optimizing the deployment of air defense weaponsand has high reference value for the researches on decision-making of combat against UAV swarm.

关 键 词：无人机集群 防空部署 嵌套粒子群优化算法 

分 类 号：V279[航空宇航科学与技术—飞行器设计]