A novel adaptive Kalman filter based NLOS error mitigation algorithm

被引：5
|
作者：
Li Qiyue [1 ]
Wu Zhong [1 ]
Li Jie [2 ]
Sun Wei [1 ]
Wang Jianping [1 ]
机构：
[1] Hefei Univ Technol, Elect Engn & Automat Dept, Hefei, Peoples R China
[2] Hefei Univ Technol, Comp & Informat Dept, Hefei, Peoples R China
来源：
IFAC PAPERSONLINE | 2015年 / 48卷 / 28期
关键词：
colored noise. Kalman filters; adaptive algorithm; ranges; measurement noise;
D O I：
10.1016/j.ifacol.2015.12.281
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this paper, we presented an algorithm for NLOS error mitigation based on adaptive Kalman filter with colored measurement noise. To eliminate NLOS error which induced by TOF-based distance measurements, a colored noise model is firstly established according to measurement noise and the filter parameters are adjusted dynamically based on the severity of NLOS environment. Then combined with adaptive Kalman filtering algorithm, the NLOS error mitigation process is adjusted in real time in order to obtain optimal estimation. The simulation experiments show that the algorithm has small error and high precision and is suitable for real-time dynamic location systems. (C) 2015, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.
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页码：1118 / 1123
页数：6
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