Research On UAV Trajectory Planning And Mission Assignment Methods

With the development of UAV technology,the good or bad trajectory planning and mission assignment of UAVs play a key role in the direction of local wars.In a complex battlefield environment,how to plan an optimal flight path around enemy radar detection and air defense threats is still a challenge.On the other hand,the study of mission assignment should not only revolve around the optimal gain,but also consider more about the reassignment strategy when the pre-assigned mission execution fails.This paper conducts research in these two directions and contains the following main elements:(1)Firstly,the models and algorithms related to UAV trajectory planning are introduced,including the modeling approach in the battlefield environment,and the 3D terrain model,radar deterrence model,anti-aircraft gun deterrence model,and weather threat model are constructed.Then the UAV’s own constraint models,i.e.,maximum range constraint,flight altitude constraint,and maneuverability constraint,and the relevant algorithms for trajectory planning,i.e.,fast extended random tree algorithm,whale optimization algorithm,and particle swarm algorithm,are defined.Then the respective advantages and disadvantages of the two communication models commonly used for UAV mission assignment,i.e.,centralized mission assignment and distributed mission assignment,are presented.The conventional model of mission assignment is further illustrated,and the probability model of ammunition loss and destruction for simulating real UAVs in combat with the enemy is proposed.(2)The trajectory planning of UAVs arriving around enemy strongholds and conducting encircling reconnaissance is investigated,and the speed of trajectory planning can be effectively improved by using two-dimensional maps for modeling the flight stability of reconnaissance UAVs.On the other hand,according to the mission scenario,the flight trajectory of the UAV arriving around the target area,and the flight trajectory surrounding the reconnaissance are treated separately.Firstly,an adaptive point selection algorithm around the target area is proposed to generate the surrounding trajectory,and then the adaptive evaluation function and the target area heuristic are proposed for the UAV trajectory planning from the starting point to the target area using the improved A* algorithm in the complex threat environment.improved A* algorithm and inflection point optimization for the planned trajectory.Simulation experiments show that it can effectively plan a better flight path to reach the target area.(3)To study the trajectory planning of UAV against enemy targets,we use 3D map modeling to define a complex battlefield threat environment,and improve the traditional sparrow search algorithm by using Halton sequence to initialize the population and adding reflection learning strategy to optimize the population in the population iteration,and make a comparison test with the performance of whale algorithm,particle swarm algorithm and traditional sparrow algorithm.The test results show that the improved sparrow search algorithm has better performance.Finally,the simulation experiments show that the sparrow search algorithm can plan a better flight path.(4)The traditional contract network algorit hm is improved to solve the task allocation problem under complex warfare situation.The joint winning strategy and emergency bidding strategy are proposed.Through comparison of simulation experiments,the improved contract network algorithm can make full use of UAV resources to plan an assignment plan with shorter mission execution time and higher mission completion rate,and it can respond and handle more timely in response to the unexpected situation of insufficient ammunition and destroyed UAVs,resulting in a better redistribution plan.