In view of the requirements of selecting the data source UAV in the networked navigation system,the ranging positioning model and data source selection problem of the clustered UAVs are studied.Based on Particle Swarm Optimization (PSO) and the chaos theory,a Chaos Particle Swarm Optimization (CPSO) is proposed.The relative distance is used to establish the discrete linear positioning model of the UAV,and the data source selection algorithm takes the Geometric Dilution of Precision (GDOP) as the fitness function.The estimation result is gradually optimized through the iteration of the velocity-position update equation.The initial population is processed by chaotic mapping,which avoids the problem of falling into the local optimal solution.The simulation results show that the proposed algorithm has higher calculation precision than PSO,and the computation time is only 14.6% of that of the traversal method.In addition,increasing the value of the learning factor within a certain range can improve the algorithm′s calculation efficiency.