Integrity Monitoring of PPP-RTK Based on Multiple Hypothesis Solution Separation

Recent progress for high-precision positioning mainly focused on PPP-RTK, which is a precise point positioning (PPP) technique based on a real-time kinematic (RTK) network. PPP-RTK is expected to become the mainstream positioning solution for various intelligent transportation systems (ITS) such as autonomous driving, unmanned aerial vehicles, and urban air mobility. Prior studies on PPP-RTK mainly focused on improving navigation accuracy. However, for safety-critical applications, integrity is also an important performance index. Since PPP-RTK is usually implemented using a Kalman filter (KF), the well-known integrity monitoring schemes developed for least-squares-based systems cannot be directly applied to PPP-RTK. After considering the time-sequential nature of KF, we propose a user-end integrity monitoring scheme of PPP-RTK based on multiple hypothesis solution separation (MHSS) to offer high-reliability and high-precision position solutions with real-time integrity information. The proposed scheme includes two key functions: real-time fault detection and rigorous protection level (PL) evaluation. This scheme captures both the faults from PPP-RTK service products and those faults introduced at the user end. Experiments are carried out with real data and simulated fault scenarios. The results suggest the effectiveness of the proposed scheme and indicate that multi-constellation PPP-RTK can offer position solutions with decimeter-level PLs (integrity risk: 10^–7/h) in open-sky areas.