Acta Geodaetica et Cartographica Sinica ›› 2024, Vol. 53 ›› Issue (1): 137-145.doi: 10.11947/j.AGCS.2024.20230101

• Geodesy and Navigation • Previous Articles     Next Articles

ARAIM availability optimization method based on dynamic particle swarm optimization algorithm

WANG Ershen1,2, SUN Xinhui1, QU Pingping1, ZENG Hongzheng3, XU Song1, PANG Tao1   

  1. 1. School of Electronic and Information Engineering, Shenyang Aerospace University, Shenyang 110136, China;
    2. College of Civil Aviation, Shenyang Aerospace University, Shenyang 110136, China;
    3. Key Laboratory of Flight Techniques and Flight Safety, Civil Aviation Flight University of China, Guanghan 618307, China
  • Received:2023-04-20 Revised:2023-11-22 Published:2024-02-06
  • Supported by:
    The National Natural Science Foundation of China (No. 62173237); The SongShan Laboratory Foundation (No. YYJC062022017); The Open Fund of State Key Laboratory of Satellite Navigation System and Equipment Technology (Nos. CEPNT2022B04; CEPNT2022A01); The Open Fund of State Key Laboratory of Dynamic Measurement Technology, North University of China (No. 2023-SYSJJ-04); The Center of Civil Aviation Satellite Application Engineering Technology (RCCASA-2022003); The Applied Basic Research Programs of Liaoning Province (Nos. 2022020502-JH2/1013; 2022JH2/101300150); The Open Fund of Key Laboratory of Flight Techniques and Flight Safety CAAC (Nos. FZ2021KF15; FZ2021ZZ06; FZ2020KF09); The Special Funds program of Shenyang Science and technology (No. 22-322-3-34)

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Abstract: Integrity monitoring technology for satellite navigation is crucial to ensuring navigation safety in the aviation field. The advanced receiver autonomous integrity monitoring (ARAIM) algorithm distributes integrity risk probabilities and continuity risk probabilities evenly among all visible satellites, resulting in a conservative vertical protection level and reduced availability. This paper proposes an ARAIM availability optimization method based on dynamic particle swarm optimization (DPSO) algorithm. By optimizing the risk probability allocation process, the vertical protection level can be effectively reduced while the same integrity indicator, thus improving the availability of the ARAIM algorithm. The proposed method was verified and compared through experiments using six globally distributed MGEX (multi-GNSS experiment) stations, and the global availability of the algorithm was analyzed. In addition, to test the practicality of the method, satellite navigation test data for the entire flight phase of an aircraft was collected at the Shenyang Faku General Aviation Airport and the algorithm was experimentally validated.The experimental results from both static and dynamic data demonstrate that the adoption of allocation strategy based on DPSO algorithm can enhance the availability of ARAIM. The coverage rate of ARAIM availability worldwide, exceeding 99.5%, has increased from 98.2% to 99.7%.

Key words: GNSS, ARAIM, availability, risk probability allocation, vertical protection level, dynamic particle swarm optimization

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