一种动态分组的多节点协同定位编队构型优化方法

Aiming at the problem of cooperative nodes selection in parallel multi-node cooperative localization, a multi-node dynamic grouping cooperative localization formation configuration optimization method based on improved genetic algorithm is proposed. A multi-node collaborative navigation model based on Cubature Kalman filtering is established by taking the inter-node ranging information as the measurement information. Considering the constraints of formation configuration and ranging information in practical system, the coding, crossover and mutation operations of standard genetic algorithms are improved. And the optimal grouping problem of the multi-node system is solved by taking the formation error bound solved by the Cramer-Rao boundary inequality as the fitness function. Formation optimization simulation experiments are carried out for cooperative systems with 10, 20, and 50 nodes, which illuminate the feasibility and effectiveness of the improved genetic algorithm. The simulation experiment results show that the formation configuration optimization method can further improve the node positioning accuracy on the basis of the fixed formation cooperative localization, and the positioning accuracy of the dynamic formation is improved by about 36% on average compared with the fixed formation.