To solve the problem of low computational efficiency of existing configuration optimization methods for collaborative navigation of clustered UAVs,this paper proposes a configuration optimization method for collaborative navigation of clustered UAVs based on the improved particle swarm optimization algorithm.Firstly,the collaborative accuracy factor is taken as the configuration evaluation standard to improve the evaluation accuracy.Based on this,the adaptive inertia factor and the asymmetric learning factor are used to improve the particle swarm optimization algorithm,which improves the optimization performance and convergence rate of the algorithm.Meanwhile,the optimal configuration is selected to improve the positioning accuracy of the clustered UAV collaborative navigation.The simulation results show that,compared with the traditional particle swarm optimization algorithm,the improved particle swarm optimization algorithm reduces the value of the collaborative accuracy factor by 33%.Based on this,the proposed method improves the positioning accuracy of user UAVs in the cluster and reduces the computational amount of configuration optimization,which is conducive to its wide application to large-scale UAV cluster.