UAV Trajectory Planning Based on PH Curve Improved by Particle Swarm Optimization and Quasi-Newton Method

Trajectory planning technology is an important foundation for the development of modern military intelligence games. This paper, based on the particle swarm optimization (PSO) and quasi-Newton method, aims to study the optimal trajectory planning of UAVs under threats such as obstacles and radar. Firstly, the five-order PH path curve in the complex number domain is established to determine the decision parameters. Secondly, in view of the shortcomings of traditional PH trajectory planning algorithms, the particle swarm optimization with directionality in the optimization process is introduced, which can iterate to a better solution at a faster rate. However, the PSO has a slower convergence speed in the later iteration, and then the quasi-Newton method is introduced to overcome its shortcomings and iterate to the optimal solution quickly. By organically combining the two algorithms, a new trajectory planning algorithm that can solve the defects of the basic PH algorithm is designed, which overcomes the shortcomings of the traditional path planning algorithm and the particle swarm algorithm. Meanwhile, the performance of the algorithm can be effectively improved. Finally, the effectiveness of our algorithm is verified by some simulation experiments.