INS-assisted inter-system biases estimation and inter-system ambiguity resolution in a complex environment

The inter-system real-time kinematic (RTK) model in which multiple systems choose the same reference satellite uses more observations than the traditional intra-system RTK model; however, it is still difficult to accurately determine the differential inter-system biases (DISB) and inter-system ambiguity in a complex environment. We propose a tightly coupled inter-system RTK/INS model that uses the high-precision position information the inertial navigation system (INS) provides to assist in DISB estimation and inter-system ambiguity resolution. Vehicle experiments on urban roads were designed to verify the effectiveness of the method. The vehicle experiments consisted of a simulated rare satellite environment with a high cutoff elevation angle and a real complex environment with buildings and trees obscuration. A robust Kalman filter strategy is used to combat the effects of multipath and non-line-of-sight signals in real complex environments. The results indicate that with the help of INS, the standard deviation of phase and code DISB is reduced by 11 and 17%, respectively, in the simulated environment and by 33 and 18%, respectively, in the real complex environment. Compared with the intra-system RTK/INS model, inter-system RTK/INS mode 3D positioning root-mean-square error is reduced by 79% in the simulated environment and by 27% in the real complex environment. In the single-epoch mode, the ambiguity success rates of the inter-system RTK/INS model, inter-system RTK model, intra-system RTK/INS model and intra-system RTK model are 89, 74, 69 and 58%, respectively, in the simulated environment, and 68, 41, 64 and 12%, respectively, in the real complex environment.