The grid strapdown inertial navigation system (SINS) used in polar navigation also includes\nthree kinds of periodic oscillation errors as common SINS are based on a geographic coordinate\nsystem. Aiming ships which have the external information to conduct a system reset regularly,\nsuppressing the Schuler periodic oscillation is an effective way to enhance navigation accuracy.\nThe Kalman filter based on the grid SINS error model which applies to the ship is established in this\npaper. The errors of grid-level attitude angles can be accurately estimated when the external velocity\ncontains constant error, and then correcting the errors of the grid-level attitude angles through\nfeedback correction can effectively dampen the Schuler periodic oscillation. The simulation results\nshow that with the aid of external reference velocity, the proposed external level damping algorithm\nbased on the Kalman filter can suppress the Schuler periodic oscillation effectively. Compared with\nthe traditional external level damping algorithm based on the damping network, the algorithm\nproposed in this paper can reduce the overshoot errors when the state of grid SINS is switched from\nthe non-damping state to the damping state, and this effectively improves the navigation accuracy of\nthe system.
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