NLOS环境中的线性回归最小二乘三维定位算法

3D Localization Algorithm Based on Linear Regression and Least Square in NLOS Environment

针对室内非视距无线环境中移动终端的三维定位问题,提出了一种非视距无线环境中基于线性回归与最小二乘法的三维定位算法。首先,基于无线通信环境中波达时间(TOA)的测量误差具有正偏置的特性,运用线性回归估计测试终端到基站之间的非视距测量距离误差与真实距离之间的线性关系;然后,根据该线性关系运用最小二乘原理对移动终端进行三维几何定位。实验结果表明,算法具有较高的定位精度,最大定位误差不超过2 m,且在非视距环境下,所提出的定位算法不仅不需要TOA的时延分布先验知识,而且定位精度优于其他基于TOA的两阶段最小二乘定位算法的定位精度。

In view of the problem of three-dimensional location of mobile terminals in indoor non-lineof-sight wireless environment,a three-dimensional location algorithm has thus been proposed based on linear regression and least square method in non-line-of-sight wireless environment.Firstly,based on the positively biased measurement error of arrival time(TOA)in wireless communication environment,the linear regression is used to estimate the linear relationship between the non-line-of-sight measurement distance error and the real distance between the test terminal and the base station.Then,combined with the linear relationship,the least square method is used to locate the 3D position of mobile terminal.The experimental results show that the proposed algorithm is characterized with a high positioning accuracy,with the maximum positioning error no more than 2 m.Moreover,in the non-line-of-sight environment,the proposed positioning algorithm does not need the prior knowledge of TOA,s time delay distribution,with the positioning accuracy better than other two-stage least squares positioning algorithm based on TOA.