A survey of GNSS receiver autonomous integrity monitoring: Research status and opportunities - Huang, Zhen; Mou, Weihua; Wang, Rui; Li, Pengpeng; Lyu, Zhicheng; Ou, Gang (Frontiers in Physics, 2025)
Integrity monitoring is crucial in applications closely related to the safety of human life and property, such as aviation, maritime navigation, autonomous driving, and rail transportation. Receiver autonomous integrity monitoring (RAIM) has attracted significant attention due to its comprehensive monitoring coverage and fast alerting capability. The paper provides a comprehensive review of RAIM algorithms for global navigation satellite system (GNSS) positioning applications. The parameters related to integrity assessment and typical fault detection and exclusion methods are reviewed, and RAIM is categorized into three types of methods: error probability distribution model-based, set representation-based, and machine learning-based. The latest state-of-the-art research, along with the strengths and shortcomings of each type of method, is presented for each type. The opportunities for the future development of RAIM are analyzed in the light of current challenges and existing results, aiming to promote further research and provide effective assurance for GNSS integrity.