Towards Centimeter-Level Positioning in Urban Environments with An Optimization-Based Tightly Coupled PPP-RTK/INS System

Precise position information plays a crucial role in industries such as intelligent unmanned systems and autonomous driving. Combining the advantages of traditional precise point positioning (PPP) and real-time kinematic (RTK) technologies, the emerging PPP-RTK technique is able to provide real-time centimeter-level positioning in open environments. However, its stability is often insufficient in complex environments due to frequent interference of satellite signals. To enhance the continuity and robustness of positioning results in such challenging environments, inertial navigation system (INS), which can perceive the motion information of the carrier, is commonly integrated with global navigation satellite system (GNSS). In this paper, an optimization-based tightly-coupled multi-GNSS PPP-RTK/INS system is proposed to achieve continuous and reliable positioning in urban environments. In the proposed algorithm, an estimator based on Maximum A Posteriori (MAP) estimation is utilized to integrate multi-GNSS raw observations, inertial measurements and precise atmospheric information. Moreover, the outlier detection algorithm based on standardized residuals is applied in the proposed method to reject gross errors introduced by GNSS observations, making the positioning results more consistent with observations to get reliable ambiguity-float solutions. Then, a cascaded ambiguity resolution is conducted to obtain final precise ambiguity-fixed solutions. The experimental results show that the proposed method achieves centimeter-level horizontal position estimates in urban environments, with an accuracy improvement of over 80% compared to PPP-RTK. Besides, the proposed optimization-based algorithm represents an accuracy improvement of approximately 30% compared to the traditional extended Kalman filter-based method.