A Fast Robust In-motion Alignment method for SINS with DVL Aided

In this paper, a fast robust in-motion alignment method is proposed for the strapdown inertial navigation system (SINS) with DVL aided. The proposed method is divided into two procedures, which are coarse alignment procedure and fine alignment procedure. In the coarse alignment procedure, an apparent velocity modeling method is investigated. Building upon this model, a robust Kalman filter (RKF) is designed for parameter estimation, then an optimal observation vector, in which the outliers of the Doppler Velocity Log (DVL) outputs are eliminated, is reconstructed. As compared with the existing method, in the proposed method, the robustness of coarse alignment procedure is enhanced. To improve the accuracy of the coarse alignment method, a fine alignment method is designed. Different from the traditional fine alignment method, the error model of the proposed fine alignment method is constructed in n 0-frame. With this advantage, the time-varying error attitude estimation for the traditional method has transformed into a time-invariant error attitude estimation. Thus, the raw data and intermediate data, which are collected in the coarse alignment procedure, can be reused in the fine alignment procedure. Take advantage of the high performance of the navigational computer, the forward-forward data processing can be carried on repeatedly, the one cycle of the forward-forward procedure consumes about 0.3 s in the real-time system. Simulation and field tests showed that the proposed method can obtain a high-accuracy initial alignment results and suppress the interference of the outliers of the DVL outputs.