Modeling and identifying of Fiber Optic Gyro Random Drift Data Based on Time Series Analysis Method

In order to effectively and quickly identify the parameters of random drifts (startup, slow and fleet) of fiber optic gyro( FOG) , the random drift of FOG is modeled as a equation of state with unknown model parameters (correlation coefficient of slow drift) , the unknown model parameters and white noise covariance of slow and fleet drifts are identified based on the time series analysis , and the coupling among three items of the random drift is computed with Kalman filter/ smoother. The real data of random drift of FOG is identified with the model to verify its applicability , and the result suggests that this method accurately compute all of the random drifts and the parameters of FOG. The present method could be used for revising navigation error of FOG as it works alone or in combination with other equipment.