摘要
在蜂窝无线定位中,由于非视距(non-line-of-sight,NLOS)误差是影响定位精度的主要因素之一,所以如何减轻NLOS误差影响成为当前无线定位研究的热点。本文针对NLOS环境下的定位跟踪问题,提出一种基于扩展卡尔曼滤波(extended Kalman filter,EKF)的定位跟踪算法。该算法首先在最小二乘准测下推导出估计测量值中NLOS误差的直接计算公式,然后使用约束加权最小二乘(constrained weighted least squares,CWLS)方法计算出每一个测量值中所含的NLOS误差,最后利用NLOS误差估计值去修正EKF滤波,以便适应NLOS环境下的定位跟踪,并获取高的定位精度。这种方式不依赖于特定的NLOS误差分布,也无需视距(line-of-sight,LOS)和非视距识别。数值结果表明该算法相比较于经典EKF算法和基于NLOS迭代的EKF算法可以快速有效地抑制定位误差,并且可以在极为恶劣的NLOS环境下满足FCC的定位要求。另外,复杂性实验表明该算法可适用于实时跟踪。
It is well known that the positioning accuracy in cellular wireless communication systems is largely affected by non-line -of-sight（NLOS） error,and thus the NLOS error mitigation algorithm has become a current hot subject of research in the wireless location field.This paper presents a robust location tracking algorithm for NLOS environment using extended kalman filtering（EKF）. The algorithm firstly deduces the formula to compute NLOS error under the least squares rule,and uses the constrained weighted least squares method directly to estimate the NLOS bias contained in each measurement range.A simply modified EKF tracking method based on NLOS correction is then applied to achieve a high accuracy for mobile location tracking.This method does not depend on a particular distribution of the NLOS error and need not line-of-sight（LOS） or NLOS identification.Numerical results illustrate that the performance of the proposed algorithm is better than that of the classic EKF and the iterated NLOS EKF algorithm.Even when base stations are all in NLOS condition,the proposed method can also meet the FCC requirement.Moreover,complexity experiments suggest that it supports real-time applications.
出处
《信号处理》
CSCD
北大核心
2010年第12期1858-1863,共6页
Journal of Signal Processing
基金
863计划(2008AA01z227)
教育部重大科技革新项目培育基金(No.706028)
关键词
扩展卡尔曼滤波
跟踪
非视距
约束加权最小二乘
extended Kalman filter（EKF）
tracking
NLOS
constrained weighted least squares
