Session B4: GNSS Integrity and Augmentation

The Protection Level for RTK/INS Loose Integrated Navigation System
Yang Sang, Aerospace Information Research (AIR) Institute, Chinese Academy of Sciences (CAS), China School of Electronic, Electricity and Communication Engineering, University of Chinese Academy of Sciences (UCAS); Xinchun Ji, Dongyan Wei, Aerospace Information Research (AIR) Institute, Chinese Academy of Sciences (CAS)
Location: Beacon B

Global Navigation Satellite Systems (GNSS) Real-time Kinematic (RTK) is recognized for its high precision and real-time capabilities. However, it faces several challenges, including susceptibility to signal obstruction and interference, as well as limitations related to low data frequency. In contrast, Inertial Navigation System (INS) offers advantages such as passive autonomy, robust anti-jamming capabilities, and high data frequency; however, the positioning error tends to diverge rapidly over time. The complementary nature of RTK and INS has made their integration a standard positioning technology in autonomous driving. The integration of GNSS and INS can be implemented through various integration modes: loose integration, tight integration, and deep integration. Compared to tight and deep integration, loose integration maintains the independence of RTK and INS. It also offers advantages such as simplicity of implementation and lower computational load, which contribute to its widespread application across various domains.
In safety-critical applications such as autonomous driving, the reliability of navigation information is paramount. Integrity is the measure of the trust that can be placed in the correctness of the information supplied by a navigation system. Integrity includes the ability of the system to provide timely warnings to users when the system should not be used for navigation. Integrity monitoring consists of two key components: fault detection and integrity risk assessment. Existing research on RTK/INS integrity monitoring predominantly focuses on tight integration mode, with limited studies specifically addressing the integrity monitoring needs of loose integration mode. In the current loose integrated navigation system, the INS is often assumed to be fault-free, while the RTK subsystem employs Receiver Autonomous Integrity Monitoring (RAIM) to detect faults and compute a protection level. However, the protection level computed by RAIM primarily represents the safety boundary of RTK positioning error and can not be used to assess the integrity risk of loose integration navigation.
To address the above problem, this study proposes a method to derive the protection level specifically for RTK/INS loose integrated navigation system based on Kalman filtering. Firstly, the study computes the derivative of the positioning error of loose integrated navigation with respect to the RAIM fault detection statistic, which is referred to as the satellite characteristic slope. By multiplying the maximum satellite characteristic slope with the fault deviation, the protection level associated with the fault deviation is established. Subsequently, the protection level due to noise is calculated by multiplying the multiple of standard deviation corresponding to the false alarm rate by the integrated positioning standard deviation. The proposed integrity protection level for loose integrated navigation is formulated as the sum of the protection levels induced by both fault deviation and noise.
This study conducted experimental validation based on measured data, demonstrating that the proposed integrity protection level for RTK/INS loose integrated navigation effectively bounds positioning error. Consequently, the protection level calculation method proposed in this paper can be utilized for integrity risk assessment in RTK/INS loose integrated navigation system. Furthermore, this method can be extended to integrity monitoring in other loose integrated navigation systems that incorporate INS. This study enhances the reliability and security of the loose integrated navigation system, with significant engineering application value.