基于散射区模型与参数聚类的室外NLOS单站定位算法

Outdoor NLOS single-station localization algorithm based on scattering area model and parameter clustering

室外非视距(non line of sight,NLOS)环境中障碍物会阻碍终端电磁波信号直接传播到基站,而且该条件下单基站收集的定位信息不足,导致定位精度不高。针对上述问题,提出一种基于空间布局的散射区模型和基于参数聚类的定位算法。根据固定基站附近的空间布局确定散射区并构建散射区模型,该算法基于该模型收集多径信号的测量参数,将k-means聚类(k-means clustering)和均值漂移聚类(means shift clustering)算法有效结合对参数聚类处理,再根据聚类结果和单站定位系统的几何结构建立方程组,将方程组的求解问题转化为非线性优化问题并利用列文伯格-马夸尔特(Levenberg-Marquardt,LM)算法求解优化问题估计目标位置。仿真结果表明,在室外NLOS环境中,且仅提供单个基站的条件下,该算法可以有效提高定位结果的精度。

In the outdoor non-line-of-sight(NLOS)environment,obstacles prevent the terminal electromagnetic signal from propagating directly to the base station,and under this condition,the location information collected by single base station is insufficient,resulting in low positioning accuracy.In order to solve the above problems,this paper proposes a scattering area model based on spatial layout and a location algorithm based on parameter clustering.The scattering areas are determined according to the spatial layout near the fixed base station and the scattering area model is constructed.Based on this model,the algorithm collects the measurement parameters of multipath signals,effectively combines k-means clustering and mean shift clustering algorithm to cluster the parameters,and then establishes equations according to the clustering results and the geometric structure of the single station positioning system.Finally,the solution problem of the system of equations is transformed into a nonlinear optimization problem,and the Lewenberg-Marquardt(LM)algorithm is used to solve the optimization problem to estimate the target position.Simulation results show that the algorithm can effectively improve the accuracy of location results under the condition that only a single base station is provided in outdoor NLOS environment.