Research On Cooperative Roundup Algorithm Of Unmanned Aerial Vehicle Swarms In Denied Environment

UAV swarm combat benefits from the advantages of high task execution efficiency,strong flexibility,and low cost,and is deemed to be the main form of combat in the future air battlefield.However,the future battlefield requires UAV swarms to have the ca pabilities of situational awareness,autonomous decision-making,and collaborative control,and to be in a position to operate in complex environments with denial features that have limited perception and communication ranges.Traditional methods and models are difficult to completely resolve the problems of rational scheduling of resources,effective avoidance of obstacles,and rounding up of targets in a communication denial environment.Therefore,this paper focuses on the resource scheduling,target round-up and obstacle avoidance,and multi-target round-up of UAV swarms in a denied environment.The main work and contributions of the paper are as following:In the context of multi-objective detection and tracking of unmanned aerial vehicle(UAV)clusters under communication denial environments,a novel method for resource scheduling based on clone immunity decision-making is proposed.Leveraging the characteristics of fast information dissemination in infectious diseases and rational decision-making in clone selection,a cluster decision activation mechanism based on infectious immunity and a cluster strategy decision mechanism based on clone selection are constructed,inspired by the relationship between the immune system and the UAV cluster combat system.The UAV cluster utilizing this method can adaptively adjust the response speed of the cluster through local perception and information exchange,and avoid targeting omission caused by aggregation due to the execution of the same strategy,ensuring the reasonable scheduling of cluster resources.Simulation results demonstrate that the UAV cluster under this method has better target detection and tracking performance in multi-objective detection and tracking scenarios compared to the ED-VS AIS method.For the cooperative target encirclement problem of UAV clusters under communication denial environments,inspired by the artificial potential field method,a self-governing encirclement method is proposed.Firstly,the speed of the target is intended for different situations.Secondly,the UAV body coordinates system under denial environments is constructed.Then,the velocity change mechanism of individual UAVs is designed to ensure that the cluster can maintain a loose formation of area detection and achieve an adaptive target encirclement formation.Finally,considering the obstacle avoidance problem in compl ex environments,the obstacle avoidance control method of UAVs and targets is intended to effectively avoid the deadlock problem that may occur in repulsive obstacle avoidance.Simulation results demonstrate that under denial environments,the UAV cluster under this method can make self-governing decisions through local information exchange,achieve obstacle avoidance,and complete single-target encirclement tasks.For the cooperative multi-target encirclement problem of UAV clusters under communication denial environments,a novel method for multi-target collaborative encirclement based on clone immunity decision-making is proposed on the basis of the cluster resource scheduling method and the self-governing encirclement method proposed in the previous two chapters.Firstly,by adjusting the strategy pool,the strategy intensity mechanism,and the "overheating" strategic judgment mechanism,the scheduling of cluster resources is achieved under the background of multi-target encirclement.Secondly,a target encirclement strategy maintenance mechanism is established to avoid the failure of the encirclement target task caused by frequent changes in the strategy.Finally,this method is increased to threedimensional space to achieve the cooperative multi-target collaborative encirclement of the cluster in three-dimensional space.Simulation results show that compared with the self-governing encirclement method without strategic scheduling,the UAV cluster under this method has stronger area detection capability and multi-target encirclement performance.