异型无人机空战对抗协同机动决策研究

Cooperative Maneuver Decision-making of Antagonistic Air Combat of Special Shaped UAV

通过异型无人机(unmanned aerial vehicle,UAV)的协同作战,可极大丰富空中作战样式,提高空战战损比.双机编队是最基本的协同作战单元,具有较大的研究价值.针对无人机协同空战可能面临的不同空中态势,分别设计歼击无人机和电子干扰无人机的机动决策模式,通过不同模式下的算法切换实现更好的协同作战.基于一致性理论设计了无人机的编队飞行与伴随干扰算法.根据动态的空战对抗特性,设计自适应的动态栅格环境,可更好地支撑路径规划与机动决策.分别使用改进的蚁群算法(ant colony algorithm,ACO)和Q-learning算法构建无人机的机动决策和冲突解脱算法,可实现无人机在空战机动的同时避免相撞事故的发生.最后以战损比为指标,通过协同空战仿真证明了协同机动决策算法的有效性.

Through the cooperative operation of special shaped UAV,it can greatly enrich the air combat pattern and improve the air combat kill-death-assist.Dual aircraft formation is the most basic cooperative combat unit,which has great research value.According to the different air situations that UAV cooperative air combat may confront,the maneuver decision-making modes of fighter UAV and electronic interference UAV are designed respectively,and better cooperative operation is realized through algorithm switching in different modes.Based on the consensus theory,the formation flight and accompanying jamming algorithm of UAV are designed.According to the characteristics of dynamic air combat,an adaptive dynamic grid environment is designed to better support path planning and maneuver decision-making.The improved ACO and Q-learning algorithms are used to construct the maneuver decision-making and conflict resolution algorithms of UAV respectively,which can realize the maneuver of UAV in air combat and avoid the occurrence of collision accidents at the same time.Finally,taking the kill-death-assist as the index,the effectiveness of the cooperative maneuver decision-making algorithm is proved by cooperative air combat simulation.