Robust Attitude and Positioning Alignment Methods for SINS/DVL Integration Based on Sliding Window Improvements

The strapdown inertial navigation system (SINS) and Doppler velocity log (DVL) are the major positioning system for underwater vehicles. The initial alignment process is the first working stage of SINS/DVL integration. Currently, the initial alignment method for SINS/DVL integration is imperfect. The major problems can be summarized in two aspects. One is the initial velocity errors and outliers of DVL outputs, which are not suppressed simultaneously. The other is the positioning uncertainty when the attitude alignment is finished. To address these two problems, robust attitude and positioning alignment methods are proposed in this article. First, a vector observation, which is based on the sliding windows improvements, is constructed for eliminating the initial velocity errors. Second, the apparent velocity motion model for the vector observation with the sliding window improvements is constructed. Based on the constructed model, a parameter estimation method, which is established by a robust Kalman filter, is proposed. Using the estimated parameters, the new observed vectors are reconstructed. Thus, the robust attitude alignment process is finished. Third, real-time and postprocessing positioning alignment methods are proposed for addressing positioning uncertainty. At last, the simulation and field tests are designed for verifying the performance of the proposed method. The test results are shown that the existing two problems are overcome.