An Improved Spherical-vector-based Particle Swarm Optimization (ISPSO) algorithm is proposed to solve the flight path planning problem of UAVs under multiple threats in complex environment.The ISPSO, combining compression factors with asynchronous learning factors, is used to find the optimal path that minimizes the cost function by efficiently searching the configuration space of the UAV via the correspondence between the particles position and speed and the turn angle and climbing angle of the UAV.To evaluate the performance of ISPSO, two benchmark scenarios are generated from real maps of digital elevation model.The simulation results show that the proposed ISPSO outperforms the spherical vector based particle swarm optimization.