REKF RAIM algorithm based on robust MM-estimation

被引：1
|
作者：
Wang W. [1 ,2 ]
Xu Y. [1 ]
机构：
[1] Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing
[2] School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing
来源：
Xi Tong Gong Cheng Yu Dian Zi Ji Shu/Systems Engineering and Electronics | 2021年 / 43卷 / 01期
关键词：
Characteristic slope; Double-fault mode; Fast satellite selection; Kalman filter; MM-estimation; Receiver autonomous integrity monitoring (RAIM);
D O I：
10.3969/j.issn.1001-506X.2021.01.26
中图分类号：
学科分类号：
摘要：
The integrity monitoring of receiver autonomous (RAIM) based on robust extended Kalman filter (REKF) algorithm is relatively ineffective in detecting and identifying the double-fault mode, especially when the fault vectors have higher spatial consistency, the robustness of M-estimation is greatly damaged. To solve this problem, the REKF RAIM algorithm based on robust MM-estimation is proposed, and MM-estimation is a two-step robust estimation method with high breakdown point and high estimated efficiency. Firstly, the least trimmed squares (LTS) estimation with high breakdown point is used to obtain the robust iterative initial value and scale parameter, and then the IGG III scheme is used to obtain the final parameter estimates, and a fast satellite selection method based on characteristic slope is designed to lower the calculation of LTS estimation. Simulation results show that MMREKF has higher robustness and better ability of detecting and identifying for double-fault mode compared with REKF based on M-estimation. © 2021, Editorial Office of Systems Engineering and Electronics. All right reserved.
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页码：216 / 222
页数：6
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