Aiming at the problems of insufficient global search ability

slow convergence speed and a tendency to fall into local optima in the standard whale optimization algorithm(WOA) in solving the UAV trajectory planning problem

an improved WOA algorithm fusing particle swarm optimization algorithm(PSO-ImWOA) is proposed.Firstly

chaotic mapping is used to initialize the population

which makes the distribution of the whale search domain more uniform

and nonlinear convergence factor is introduced to solve the problem of convergence speed.Then

PSO algorithm

which has a strong optimization capability

is introduced into the exploration and development stages of the WOA

and the dynamic inertia weight factor is used to balance global exploration and local development capabilities of the algorithm.Finally

the mutation perturbation generates a new solution

and then accepts the suboptimal solution with the help of simulated annealing algorithm

which successfully circumvents the dilemma of falling into local optima.The simulation results show the superiority and effectiveness of the improved algorithm in trajectory planning.