Robust extend Kalman filtering method based on precise relative positioning by using multi-constellation integrated system

被引：0

作者：

Gao, Xiao ^{[1
,2
]}

Dai, Wujiao ^{[1
]}

Zhang, Chao ^{[1
]}

Yu, Wenkun ^{[1
]}

机构：

[1] School of Geoscience and Info-Physics, Central South University, Changsha,410083, China

[2] Northwest Electric Power Design Institute Co., Ltd. of China Power Engineering Consulting Group, Xi'an,710032, China

来源：

Wuhan Daxue Xuebao (Xinxi Kexue Ban)/Geomatics and Information Science of Wuhan University | 2015年 / 40卷 / 10期

关键词：

Actual measurements - Extend Kalman filter - High-quality observations - Integrated Positioning - Kalman filtering method - Positioning accuracy - Relative positioning - Robust estimation;

D O I：

10.13203/j.whugis20130668

中图分类号：

学科分类号：

摘要：

The extended Kalman filter method is effective in multi-constellation integrated systems, but its application is restricted because the method demands high quality observations. Due to the fact that the classical EKF method will seriously degrade because of observation outliers, this paper studies the robust EKF method based on IGGIII model and determines the value ranges of fractile factors using actual measurement data from the integrated GPS/GLONASS/BDS system. Three masks are used to simulate the complex user observation environment, which are helpful when investigating the application of robust EKF method in precise relative positioning. Results show that the robust EKF improves the fix-rate for ambiguity and positioning accuracy. ©, 2015, Wuhan University All right reserved.

引用

页码：1329 / 1333