Fault Detection and Exclusion for Cooperative Vehicles Navigation under High-Precision Positioning

The trend of urbanization has increased the demand for highly available public transportation. In order to meet these demands in urban areas, Intelligent Transportation Systems (ITS) aim to improve capacity and safety while reducing costs, accidents, and environmental impact. Integrity monitoring is a key issue in intelligent transportation positioning based on the Global Navigation Satellite System (GNSS). Accurate monitoring and exclusion of faults in GNSS measurements greatly enhance the stability of positioning performance and lay the foundation for the secure critical applications of GNSS. However, existing traditional fault detection algorithms mainly rely on pseudorange measurements, which are unable to meet the accuracy and integrity requirements for operation in complex urban environments. Therefore, it is necessary to utilize carrier phase measurements for high-precision positioning. This paper proposes a fault detection and exclusion algorithm based on carrier phase residual values to eliminate early faults. By using Real-Time Kinematic (RTK) positioning technology, atmospheric propagation errors are eliminated by double-difference measurements, and carrier phase residual values for ambiguity-fixed solutions are extracted. A Gaussian Mixture Model (GMM) is then used to fit the residual distribution without faults, and a fault detection method is proposed based on this. The effectiveness of the algorithm is verified through extensive vehicle experiments with artificially injected faults. This research is of significant importance for GNSS-based intelligent transportation vehicle positioning.