Applicability compensation method for random drift of fiber optic gyroscopes

Based on the limitation of founding a time-sequence model and using Kalman filter to wipe off the random noise, an adaptive Kalman filtering arithmetic for on-line compensation of the random errors of fiber optic gyroscope (FOG) was presented. As emerging error in a time-sequence model, the time-varied model and unknown noise can be compensated by introducing a pseudo noise. Consequently, an appropriate high-precision filter was designed for the FOG inertial navigation system. The Allan variance was utilized to analyze the output of FOG, and some main noise of FOG can be extracted and confirmed, then the performance and precision of the time-sequence model of FOG can be evaluated. The practical data of FOG was analyzed. It is shown that the main random noise of FOG are the angular rate ramp, the rate random walk and the bias instability, and the proposed adapted Kalman filter arithmetic can adapt to the time-varied characteristic of the FOG drift, and it is an effective method for FOG to wipe off it's random drift noise.