Existing methods for positioning UAV clusters often rely on satellite navigation or high-precision anchors.However,when the UAV cluster operates in areas with satellite signal interfer-ence,the overall positioning accuracy of the cluster can be severely affected.Therefore,research on cluster geometric configuration is crucial for distributed UAV cluster collaborative navigation technologies that do not rely on satellites or high-precision anchor machines.To address the issues of improving the positioning accuracy and optimizing the configuration of distributed clusters,a method for optimizing the geometric configuration of distributed clusters is proposed.First,the position dilution of precision(PDOP)factor of node positions is calculated.Then,a set of evalua-tion criteria for the optimal geometric configuration of distributed UAV clusters is proposed,in-cluding criteria for maximising cluster positioning accuracy,balancing individual positioning accu-racy,and balancing communication distances.These criteria are used to achieve a holistic optimi-zation of the cluster configuration.Next,the LambdaLR function is used to improve the velocity update formula of the particle swarm optimization(PSO)algorithm by adjusting the inertia weight and learning factor.Based on this algorithm,the overall positioning accuracy of the cluster is esti-mated and optimized.The simulation results show that the proposed method exhibits high robust-ness in optimizing cluster configurations of different scales and meets the real-time requirements for distributed large-scale cluster configuration optimization solutions.The improved PSO algo-rithm achieves optimization effects ranging from 3.31％to 8.54％in terms of the average node PDOP compared to standard PSO.
维普
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