LTE中抑制非视距误差的分层协同定位算法

针对长期演进技术(LTE)定位系统中非视距(NLOS)误差会使得用户终端测得的定位参数存在较大偏差,从而导致基于观测到达时间差(OTDOA)定位技术所估计的用户终端位置定位精度下降,以及传统Chan算法和Taylor级数展开算法中OTDOA协方差矩阵难以获取的问题,本文提出了一种抑制NLOS误差的分层协同定位算法(HCLA, hierarchical collaborative localization algorithm)。算法首先鉴别出含NLOS误差的基站,然后利用残差加权算法获取OTDOA协方差矩阵,再对传统的Chan算法和Taylor级数展开算法进行改进,将二者联合起来对用户终端进行分层协同定位。该算法无需知道OTDOA误差先验信息。仿真结果表明,在NLOS环境下该算法能准确鉴别出含NLOS误差的基站,并能有效减小定位误差。

The hierarchical collaborative localization algorithmfor non-line-of-sight error mitigation in LTE cellular network

In LTE (Long Term Evolution) system, NLOS (Non-line of sight) error can lead to a large deviation of the position parameters measured by UE (User Equipment), resulting in a decrease of the position accuracy of estimated UE based on the OTDOA (Observed Time Difference of Arrival) positioning technology. OTDOA covariance matrix is difficult to be obtained in the traditional Chan algorithm and Taylor series expansion localization algorithm. To solve this problem, a hierarchical collaborative localization algorithm (HCLA), which can mitigate the NLOS error, is proposed in this paper. Firstly, the eNodeB that includes NLOS error is identified, then the OTDOA covariance matrix is obtained using the residual weighting algorithm, and then the Chan algorithm and Taylor series expansion algorithm are improved, finally, the two methods are combined to make hierarchical collaborative localization of UE. This algorithm can run without the priori information of OTDOA error. Simulation results show that, in NLOS environment, the eNodeB that contains NLOS error can be accurately identified, and the position error can be effectively reduced.