近邻点联合测距修正粒子群优化定位算法

PSO localization algorithm based on joint ranging modification of neighbor node

针对在信标节点随机分布的环境中传统测距差分修正定位算法对参考节点选取过于单一,导致测距修正系数误差较大的问题,提出了一种近邻点联合测距修正粒子群优化的定位算法。它利用一种近邻点联合测距修正算法得到未知节点到各信标节点的修正距离,然后通过一种改进的粒子群优化(PSO)算法对定位结果进行优化,得到未知节点的估计位置。仿真结果表明:改进定位算法与传统算法相比,有效地提高了定位精度和稳定性。

Aimed at the problem that in the beacon nodes randomly distributed environment,reference node selection by traditional difference correction localization algorithm is too single,which cause that ranging modification coefficient has big error,propose a PSO localization algorithm based on joint ranging modification of neighbor node. The algorithm uses a joint ranging modification algorithm of neighbor node to get the modified distance from the unknown node to each beacon node,and then use an improved PSO algorithm to optimize the positioning result,obtain estimated position of unknown node. Simulation results show that the proposed algorithm has obvious improvement of positioning precision and achieve good stability,compared with traditional positioning algorithm.