ARAIM Protection Level Optimization Method Based on Sparrow Search Algorithm

Ming Mu, Hongxia Wang, Kelin Zhong, Kun Fang, Zhipeng Wang

Abstract:	Based on the multiple hypothesis solution separation (MHSS), Advanced Receiver Autonomous Integrity Monitoring(ARAIM)uses integrity support message (ISM) parameters for fault monitoring, providing Localizer Performance with Vertical Guidance for precision approach as low as 200ft (LPV-200). The baseline algorithm of ARAIM only optimizes the allocation of integrity risk, and its protection level is relatively conservative. The integrity requirements of LPV-200 cannot always be met, resulting in the poor availability of LPV-200. In order to address this issue, this paper proposes a protection level optimization method based on the sparrow search algorithm (SSA). The proposed method can simultaneously optimize the allocation of integrity risk and continuity risk, as well as the position solution, thereby improving the performance of ARAIM. Simulation results show that the proposed method can reduce the vertical protection level (VPL), and improve the availability of LPV-200 for dual constellation scenarios. Compared with the baseline algorithm, the availability coverage increased by 23.45% for the constellation combination scenario of GPS and Galileo, and by 19.28% for the GPS and BDS combination scenario. Moreover, the optimized VPLs are computed using flight trial data to evaluate the performance of ARAIM for flight scenarios. Results show that the VPLs can overbound positioning errors effectively, ensuring the integrity performance of ARAIM.
Published in:	Proceedings of the 2024 International Technical Meeting of The Institute of Navigation January 23 - 25, 2024 Hyatt Regency Long Beach Long Beach, California
Pages:	326 - 337
Cite this article:	Mu, Ming, Wang, Hongxia, Zhong, Kelin, Fang, Kun, Wang, Zhipeng, "ARAIM Protection Level Optimization Method Based on Sparrow Search Algorithm," Proceedings of the 2024 International Technical Meeting of The Institute of Navigation, Long Beach, California, January 2024, pp. 326-337. https://doi.org/10.33012/2024.19501
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