A Robust INS State Initialization Method for Vehicular GNSS/MEMS-INS Integrated Navigation in Urban Environment

Accurate and rapid INS state initialization is crucial to ensure the performance of vehicular GNSS/INS integrated navigation. However, in typical urban environments (such as under viaducts and urban canyons), existing GNSS-assisted INS state initialization methods are sensitive to observation outliers. This paper proposes a robust INS state initialization method for vehicle-mounted GNSS/INS integrated navigation. The proposed method first derives the error propagation between the short-term relative navigation (i.e., position, velocity, attitude) and the INS initial state and the GNSS observation error model; then, the high-precision relative pose generated by INS is used to construct constraints between GNSS observation sequences, and the INS state initialization problem is converted into an optimization problem; finally, a two-step optimization strategy is designed to improve the problem of high computational complexity in solving the full-state optimization problem. We use six datasets collected in a typical urban environment to verify the feasibility of the proposed method. The proposed method uses observation sequences within a 10-second to initialize the heading, velocity, and horizontal position with errors of 2.50°, 0.30 m/s, and 11.1 m, respectively, which are reduced by 73%, 41%, and 14% compared with existing methods.