Research on the Data Fusion Theory Applying in the Compensation of Gyroscope Drift

In order to improve the stability and control performance of the Opto-Electric platform, aiming at the fiber optic gyro sensors, which is used in the feedback loop of the platform, we study the data fusion of the current angular velocity measurement, historical gyro output and random drift to do the drift compensation. Adopt double regression model to determine the polynomial equation of both fiber optic gyro output and the random drift. Take the current gyro output as measurement, and combine the history gyro output and the random drift to the state equation, then apply kalman filter algorithm to compensate the random drift online. The experiment results show that the AR model fits the gyro random drift very well, the fitting rate can reach 90%, and with compensation the random drift reduces to one over ten. The method can restrain the fiber optic gyro random drift of three-axis platform, and the drift compensation rate is around 80% similar to 90%.