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Modeling and Compensation for Dynamic Random Error of Accelerometer under Mooring State

The dynamic random error generated by the accelerometer in the ship mooring state will decrease the attitude alignment accuracy of the inertial navigation system. In order to improve the alignment accuracy, this paper proposes a dynamic random error modeling and compensation method based on non-stationary time series model and Kalman filter. Firstly, through the analysis of acceleration test data, the non-stationary time series model reflecting the random characteristics of data is established, and the corresponding kalman filter is designed based on this model. The processing results of measured data on high-precision turntable show that the proposed method can effectively suppress the dynamic random error of the accelerometer under the condition of periodic angular motion.