RVC-RTK: Resilient velocity-constrained framework for GNSS real-time kinematic positioning

Abstract Global Navigation Satellite System (GNSS) real-time kinematic (RTK) positioning can provide accurate and reliable location services. Previous studies have investigated RTK algorithms constrained by carrier velocity information, whereas limited attention has been paid to the resilient refinement of carrier velocity information and motion states. In this study, a resilient velocity-constrained RTK framework for GNSS RTK (RVC-RTK) is proposed. Specifically, the proposed RVC-RTK resiliently integrates the velocity estimates from both time-differenced carrier phase (TDCP) and time-differenced pseudorange (TDPR) methods. Then, a sliding window strategy is adopted to refine reliable multi-epoch velocity estimates and further classify the receiver motion states. On this basis, resilient velocity constraints are imposed according to different motion states. Experiment results reveal that the accuracy of TDPR velocity estimates is 0.234, 0.279, and 0.317 m/s in X, Y, and Z components, respectively, while a higher accuracy of 0.008, 0.011, and 0.008 m/s is achieved for TDCP velocity estimates. This demonstrates the feasibility of introducing velocity constraints to improve the RTK positioning. Compared to the traditional RTK algorithm, the proposed RVC-RTK framework improves the positioning accuracy by 38.1%, 53.8%, and 23.5% in east, north, and up components, respectively. In conclusion, the proposed RVC-RTK framework can effectively improve the RTK positioning performance in real kinematic applications.