In this paper, the Allan variance technique is used in analyzing the output signal of a fiber optic gyroscope, by which the characteristics of the noise terms in the angular velocity data was determined. Then we process the random drift data of the FOG with a Kalman Filter based on the theory of time series analysis. On the other hand, an LMS adaptive filter is also applied to the random drift data. Comparative analysis on the filtering effect and their advantages and disadvantages of both algorithms is carried out. The results show both algorithms has a certain role on suppressing the random drift of the gyroscope, and the LMS adaptive filter is more effective and has a better adaptability in practice.
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