A MFKF Based SINS/DVL/USBL Integrated Navigation Algorithm for Unmanned Underwater Vehicles in Polar Regions

To conquer the high-accuracy navigation of Unmanned Underwater Vehicles (UUV) in polar regions, an integrated navigation algorithm based on the strapdown inertial navigation system (SINS) is proposed in this paper. Considering that the traditional SINS is based on the north-oriented geographic frame and will lose efficacy in polar regions because of the meridian convergence, the grid frame is employed to solve the problem of meridian convergence. Then the grid SINS still contains periodic oscillation errors and accumulated errors, so the Doppler velocity \log log (DVL) and ultra-short base line (USBL) are employed as the measurements to restrain the grid SINS errors and improve the navigation accuracy, and the grid SINS/DVL/USBL integrated navigation filter model is established. Finally, the DVL and the USBL have different update frequency and the sparse USBL output will decrease the estimation frequency and accuracy of the filter, and a multi-frequency Kalman filter (MFKF) is explored to maintain the high and stable update frequency and estimation accuracy. Simulation experiment results show that the proposed grid SINS/DVL/USBL integrated navigation algorithm can restrain the grid SINS errors effectively and navigate the UUVs in polar regions with high accuracy.