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A Receiver Autonomous Integrity Monitoring Algorithm Based on Variance Inflation Model
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Jian WANG1, Le WANG1, 2, 3, *, Guanwen HUANG1, 2, 4, Ziwei WANG1, Weicong YANG1
Journal of Geodesy and Geodynamics | 2025, 45(10) : 1049 - 1056
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Journal of Geodesy and Geodynamics | 2025, 45(10): 1049-1056
A Receiver Autonomous Integrity Monitoring Algorithm Based on Variance Inflation Model
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Jian WANG1, Le WANG1, 2, 3, *, Guanwen HUANG1, 2, 4, Ziwei WANG1, Weicong YANG1
Affiliations
  • 1 School of Geological Engineering and Geomatics, Chang'an University, 126 Yanta Road, Xi'an 710054, China
  • 2 Engineering Research Center of Intelligent BDS, Universities of Shaanxi Province, 126 Yanta Road, Xi'an 710054, China
  • 3 Academy of Yellow River Sciences of Shaanxi Province, 126 Yanta Road, Xi'an 710054, China
  • 4 Key Laboratory of Ecological Geology and Disaster Prevention, MNR, 126 Yanta Road, Xi'an 710054, China
  • WANG Jian, postgraduate, majors in GNSS integrity monitoring, E-mail:

About Author:

WANG Jian, postgraduate, majors in GNSS integrity monitoring, E-mail:

Published: 2025-10-15 doi: 10.14075/j.jgg.2024.09.442
Outline
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To address the limitations of traditional RAIM algorithms, including abnormal fault detection and insensitivity to small faults, we introduce the concept of variance inflation from robust estimation into receiver autonomous integrity monitoring(RAIM). A RAIM algorithm combing variance inflation model is proposed, with an improved fault handling process. Integrity determination is performed using the user's protection level based on positioning uncertainty, and multi-constellation simulations and real-world tests in complex environments are conducted. The simulation results show that the proposed method can accurately detect a significant fault of 30 meters and effectively mitigate the impact of a small 5-meter fault on positioning results, successfully restoring the positioning error level to the state before the fault is introduced. The real-world test results show that the proposed method achieves horizontal and vertical availability rates of 95.38% and 98.74%, respectively, which are 11.63% and 5.06% higher than traditional RAIM algorithms. In terms of positioning accuracy, compared to traditional RAIM algorithms, the proposed method improves precision in E, N, U directions by 23.03%, 11.68%, and 26.79%, respectively.

receiver autonomous integrity monitoring(RAIM)  /  variance inflation  /  fault handling  /  protection level  /  availability
王建, 王乐, 黄观文, 王紫薇, 杨维聪. 一种联合方差膨胀模型的接收机自主完好性监测算法. 大地测量与地球动力学, 2025 , 45 (10) : 1049 -1056 . DOI: 10.14075/j.jgg.2024.09.442
Jian WANG, Le WANG, Guanwen HUANG, Ziwei WANG, Weicong YANG. A Receiver Autonomous Integrity Monitoring Algorithm Based on Variance Inflation Model[J]. Journal of Geodesy and Geodynamics, 2025 , 45 (10) : 1049 -1056 . DOI: 10.14075/j.jgg.2024.09.442
  • National Natural Science Foundation of China(42374025)
  • Key Research and Development Program of Shaanxi Province(2021LLRH-06)
  • Key Research and Development Program of Shaanxi Province(2022ZDLSF07-12)
  • Key Research and Development Program of Shaanxi Province(2022KW-09)
Year 2025 volume 45 Issue 10
51
25
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Article Info
doi: 10.14075/j.jgg.2024.09.442
  • Receive Date:2024-09-20
  • Online Date:2026-10-29
  • Published:2025-10-15
Article Data
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History
  • Received:2024-09-20
Funding
National Natural Science Foundation of China(42374025)
Key Research and Development Program of Shaanxi Province(2021LLRH-06)
Key Research and Development Program of Shaanxi Province(2022ZDLSF07-12)
Key Research and Development Program of Shaanxi Province(2022KW-09)
Affiliations
    1 School of Geological Engineering and Geomatics, Chang'an University, 126 Yanta Road, Xi'an 710054, China
    2 Engineering Research Center of Intelligent BDS, Universities of Shaanxi Province, 126 Yanta Road, Xi'an 710054, China
    3 Academy of Yellow River Sciences of Shaanxi Province, 126 Yanta Road, Xi'an 710054, China
    4 Key Laboratory of Ecological Geology and Disaster Prevention, MNR, 126 Yanta Road, Xi'an 710054, China
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表12种不同金属材料的力学参数
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多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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