Random drift error of fiber optic gyroscope is the crucial factor that influences the calculation accuracy of the attitude of airborne vector gravimetry. Modeling and compensating it can restrain this type of error significantly. Given the problem that traditional ARMA model can be only applied in the case of stable random drift, which cannot meet the need of real-time filtering, an ARIMA model (autoregressive integrated moving average) which is suitable for non-stable random drift is introduced along with the detailed procedure in this paper. The algorithm that can eliminate the constant component of original sampling sequence with real-time averaging method is also proposed as well as the real-time Kalman filtering estimation of the random drift. With the methods proposed above, the variance of random drift can be reduced by 46.5%. The analysis of Allan variance suggests that the coefficients of random drift for angle and angular speed have decreased about 50% and 40%, respectively. The results showed that non-stable random drift can be accurately characterized by ARIMA model and that online estimation of random drift can be realized by real-time average algorithm, indicating the potential to improve the calculation accuracy of the attitude of airborne vector gravimetry.
WANG Zheng
,
LI Jiancheng
. Research on the Real-time Compensation of the Fiber Optic Gyroscope Random Drift in Airborne Vector Gravimetry[J]. Acta Geodaetica et Cartographica Sinica, 2017
, 46(2)
: 144
-150
.
DOI: 10.11947/j.AGCS.2017.20160174
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