基于卡尔曼滤波的测量值重构及定位算法

黄清明; 刘琚

doi:10.3724/SP.J.1146.2005.01552

基于卡尔曼滤波的测量值重构及定位算法

doi: 10.3724/SP.J.1146.2005.01552

黄清明^①;刘琚,
刘琚

基金项目:

国家自然科学基金(60572105)，综合业务网国家重点实验室基金(ISN7-02)，移动通信国家重点实验室开放基金(A2005008)和教育部新世纪优秀人才支持计划 (NCET) 资助课题

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出版历程
- 收稿日期: 2005-12-01
- 修回日期: 2006-05-24
- 刊出日期: 2007-07-19

Tracking Based on Kalman Filtering for Measurements Restructuring and Mobile Location

Huang Qing-ming^①;刘琚,
Liu Ju

摘要

摘要: 在蜂窝网无线定位技术中，非视距(NLOS)误差的存在使定位性能急剧下降。该文提出了一种针对NLOS环境的基于卡尔曼滤波(KF)的动态跟踪定位算法。算法首先利用有偏卡尔曼滤波器的对测量值进行重构，然后利用重构后的测量值进行卡尔曼定位，并引入推算机制加以修正。实验结果表明，该方法在极为恶劣的NLOS环境下也能够获得很高的定位精度。
- 无线定位;卡尔曼滤波;非视距误差
Abstract: The main impairment for location of terminals in wireless communications system is the Non-Line Of Sight (NLOS) condition. This paper presents a robust location tracking architecture for a NLOS situation. It mitigates NLOS error in the raw measurement using biased Kalman filtering. And then, a reckoning mechanism is introduced to Kalman filtering of location estimates. Simulation results demonstrate that, with the novel architecture, the location estimate can be obtained with good accuracy even in severe NLOS propagation conditions.

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参考文献(1)

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