Research On Joint Optimization Of Regional Coverage Of Flight Self-organizing Network And UAV Cluster Structure

In recent years,with the rapid development of the small embedded system and wireless communication technology,small UAV technology has developed rapidly.Thanks to the advantages of low cost,strong mobility,and high concealment,small UAVs have been widely used in civil and military fields,such as agricultural monitoring,logistics transportation,military patrol,logistics transportation,and so on.Compared with the traditional large-scale single UAV system,the small UAV cluster system has stronger anti destruction and more reliable ability.The path planning algorithm of UAV is the basis for UAV cluster to complete tasks efficiently,and the clustering algorithm of UAV cluster is an effective method to maintain the stability of UAV flight self-organizing network in UAV cluster structure control scheme.At present,how to realize the rapid coverage of 3D area of UAV is an important and unsolved problem.The improvement of 3D area coverage speed will increase the distance between UAVs,and then affect the stability of UAV cluster communication.Based on these two problems,this paper will jointly optimize the UAV cluster from two aspects: the 3D area coverage of the UAV and the structural control of the UAV cluster.The main work of this paper is as follows:1)According to whether the path generated by the path planning algorithm conforms to the flight characteristics of fixed-wing UAV,this paper analyzes whether the commonly used path planning algorithm can be used in the real scene.Then it analyzes the limitations of the clustering algorithm used in UAV clusters from the aspect of use scenario.Finally,the commonly used path planning algorithms are expanded in three dimensions to study the fast coverage ability of these algorithms in 3D area.2)In order to solve the problems faced by UAV clusters in 3D area coverage and patrol,a 3D pheromone UAV smooth path planning algorithm is proposed based on 3D space discretization.The algorithm establishes a dynamic change model of pheromone concentration,uses pheromone concentration sniffing to guide the UAV to path in 3D space,and smooths the UAV flight trajectory by establishing the maximum steering angle criterion.The simulation results show that the time taken by this algorithm to cover the whole space is 61.4% of that of other fastest coverage model algorithms.The coverage proportion of patrol scenes is 15%higher than that of other model algorithms and solves the phenomena of sharp turn and emergency stop in other UAV path planning algorithms.3)Based on the 3D pheromone UAV smooth path planning algorithm,inspired by Brownian motion and gravity,a movement control clustering algorithm based on coverage and patrol is proposed.The algorithm combines the mobility scheme based on 3D fast coverage and the clustering scheme to maintain the stable communication link between UAVs.It realizes the rapid coverage of 3D space under the condition of ensuring the stability of UAV cluster communication.The simulation results show that when the cluster control effect is 1.37 times that of other algorithms,the 3D area coverage of the UAV cluster is guaranteed,and the free UAV accounts for only 4% of the UAV cluster.