Research On Cooperative Tracking Strategy Of UAV Swarm Based On Bionic Model

With the advancement of science and technology around the world,future air operations will show the characteristics of high unmanned autonomy,intelligent swarm coordination and large-scale operations,which will greatly increase the complexity of the future air battlefield and pose challenges to air combat equipment situational awareness,target tracking and anti-jamming capabilities in complex environments.Among them,the UAV swarm has become the main combat form in the future air battlefield.This paper takes UAV swarm as the research object,focusing on the problem of swarm cooperative target tracking,which mainly involves the problems of UAV swarm target detection,target tracking and tracking trajectory planning.The main work of the paper is as follows:(1)For the target detection problem of UAV swarm,a collaborative target detection strategy of UAV swarm based on the bionic infectious diseases model is proposed by taking advantage of the rapid spread of infectious disease information.By analyzing the biological mechanism of infectious disease transmission,a bionic infectious disease model is established.The model includes four sub-processes:direct-infection,cross-infection,immune repair,and virus accumulation.Further mapping to the swarm target detection,target information can be rapidly transmitted within the swarm under the function of data-driven,so that the whole swarm can respond quickly and accurately while maintaining coordination.The simulation results based on the target tracking background show that the UAV swarm under the action of the model achieves continuous detection of a moving target.(2)For the target tracking problem of UAV swarm,a cooperative target tracking strategy of UAV swarm based on the bionic immune model is proposed by referring to the immune response and self-regulation mechanism of biological response to virus invasion.By analyzing the working mechanism of the immune system,a biological immune model is established,which includes antibody production mechanism,antibody selection mechanism and immune cells regulation mechanism.Using the antibody selection mechanism to select suitable UAVs for target tracking can not only complete the task of target tracking,improve the accuracy of target tracking,but also reduce the consumption of UAV swarm resources.The simulation results prove that the UAV swarm under the action of this model can effectively track the target and maintain the formation during the tracking process.(3)For the tracking trajectory planning problem of UAV swarm,the paper proposes a swarm trajectory planning strategy based on infection-immune bionic optimization to ensure that UAVs can safely pass through the obstacles and achieve effective tracking of a target.By analyzing the mechanisms of virus infection and the individual immune,an infection-immune bionic optimization strategy is established.The strategy is applied to the trajectory planning of UAV swarm tracking,and individuals with absolute immunity are used to model the obstacle area,while individuals without absolute immunity could model the obstacle free area.With the virus update mechanism,the route with maximum virus capacity can be generated after multiple transmissions.Simulation results show that the proposed algorithm has faster convergence speed and better optimization effect than ant colony algorithm.