摘要
在蜂窝网络中,非视距(NLOS)传播是影响定位精度的主要因素。针对LOS与NLOS的混合环境,提出了一种基于到达时间(TOA)测量值进行NLOS误差消除的算法。该算法首先利用TOA测量值的统计特征建立新的判决机制,鉴别当前时刻的测量值是否存在NLOS误差,然后对包含NLOS误差的测量值,通过构建测量误差模型估计NLOS误差,并以此修正卡尔曼滤波器的新息,实现LOS重构。仿真结果表明,与已知算法相比,文章提出的算法能够更好地抑制NLOS误差,并且适应于不同的LOS与NLOS混合环境。
The main impact on location of mobile terminals in cellular network is the Non-Line-of- Sight （NLOS） propagation. Based on modified Kalman Filter, an algorithm of mitigating NLOS error under LOS/NLOS conditions is proposed. The NLOS error is first identified by exploiting the statisti- cal characteristics of the time history of range measurements, and the NLOS error in current range measurements is also estimated according to the relationship between range measurements and error. Then, the Kalman Filter uses the estimated value to adjust its renewal process. Simulation results demonstrate that, compared with traditional algorithms of NLOS error mitigation, the proposed meth- ods can mitigate NLOS error in range measurements more effectively under LOS/NLOS condition.
出处
《信息工程大学学报》
2014年第2期175-180,共6页
Journal of Information Engineering University
基金
国家科技重大专项资助项目(2011ZX03003-003-02)
关键词
到达时间
非视距误差
卡尔曼滤波
视距重构
time of arrival
non-line-of-sight error
Kalman filter
LOS reconstruction
