基于稳健MM估计的REKF RAIM算法

doi:10.3969/j.issn.1001-506X.2021.01.26

Abstract

Abstract:

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.

Key words: Kalman filter, receiver autonomous integrity monitoring (RAIM), MM-estimation, double-fault mode, characteristic slope, fast satellite selection

CLC Number:

V249.31

Wenbo WANG, Ying XU. REKF RAIM algorithm based on robust MM-estimation[J]. Systems Engineering and Electronics, 2021, 43(1): 216-222.

Figures/Tables 7

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监测算法	伪距偏差
监测算法	30	50	80	100
EKF RAIM	5.428	5.711	6.284	6.754
REKF RAIM	4.423	4.496	4.802	5.028
所提方法	3.945	3.952	3.934	3.936

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REKF RAIM algorithm based on robust MM-estimation

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