A Coupled RTK/INS Positioning Method Based on Robust Estimation

In the urban environment, the positioning results of RTK/INS integrated navigation are often influenced by grosses, which degrades the positioning accuracy and damages the stability of the navigation system. To solve this dilemma, a loose coupled RTK/INS positioning method based on robust estimation is proposed. Firstly, during RTK positioning, for eliminating corrupted measurements caused by Non-Line-of-Sight (NLOS) signals and multipath, this paper researches the RTK positioning algorithm based on bifactor robust estimation. In this method, the ambiguity is fixed and solved back into the Double-Difference (DD) equation in least square model. The posterior residual vector is used for the bifactor robust processing to eliminate the influence of some abnormal observations. Then, the RTK positioning results are loosely integrated with Inertial Navigation System (INS), and the robust processing based on Huber equivalent weight function is implemented in the process of the Kalman filter update. Finally, the proposed algorithm is validated by vehicle data in a typical urban environment. The experimental results show that compared with the traditional least squares-based RTK, the accuracy of the bifactor RTK method is improved by 2.48 cm in the horizontal direction. Meanwhile, in contrast with the RTK/INS method based on the single robust processing, the accuracy of the proposed robust bifactor error method in the horizontal direction is increased by 3.85 cm. The navigation accuracy and reliability are significantly enhanced. In dynamic environment, this research has certain theoretical reference and practical value for vehicular and autonomous driving applications.