Research on GNSS-Assisted Low-Cost INS Combined Navigation Moving Base Initial Alignment Technique

Aiming at the initial alignment problem of low-cost INS/GNSS in the case of moving base, this paper proposes a set of GNSS-assisted low-cost INS combined navigation initial alignment schemes, which is designed, optimized, and verified. Firstly, this paper analyses the impact of accelerometer zero bias on the accuracy of multi-vector construction and proposes an improved vector construction method, which approximates the suppression of the error caused by the accelerometer zero bias accumulating over time by vector subtraction instead of sliding window integration and also overcomes the impact of the OBA algorithm’s computational increase and memory occupation caused by the fact that the sliding window integration needs to store and integrate the data in the window. Secondly, this paper also designs an improved Kalman filter model to reconstruct the state equation and measurement equation of the system, which can more accurately estimate the zero bias of the gyroscope online and compensate for the misalignment angle of the carrier system by using the velocity and position information of the GNSS, eliminating the influence of the zero bias of the gyroscope on the accuracy of the multi-vector, and improving the accuracy of the initial alignment of the moving base and the robustness of the algorithm. Finally, the algorithm proposed in this paper and other algorithms are compared and analyzed in simulation and vehicle test experiments. The simulation experiments verify the feasibility of the initial alignment method proposed in this paper; the vehicle test experiments use vector subtraction and sliding window integration to construct the multivector, and then estimate the zero bias of the gyroscope and compensate for the misalignment angle of the carrier system by using Kalman filtering model proposed in this paper and other Kalman filtering models, respectively. The measured results show that the proposed method has better alignment accuracy and algorithm robustness than the existing Optimization-based alignment and their improvement algorithms for the moving base of low-cost INS/GNSS combined navigation.