Research On The Random Drift Model And Filter Method Of Spaceborne Fiber Opticgyro

Traditiona l mecha nical gyro SINS and laser gyro SINS have disad vantages suchas bulky, heavy, low reliability, and so on. FOG SINS can make up for thesedeficiencies, so it is used widely in satellite navigation system. One of the ma infactors affecting the accuracy of the system is that the drift of FOG increase s withtime.In order to improve the precision of satellite attitude determination, the paperanalyzes the noise source of FOG, and inspects the data of the random drift throughstatistica l test including stability test, period ic test and norma l test. After the datapretreatment, the regression model and the auto-regression moving model isestablished through the time series analysis theory. And then, the data of the FOGrandom drift is processed by Kalma n filter.In addition, wavelet analysis is a time-frequency analysis method with multiresolutionanalysis capability, which is suitable for non-sta tionary signa l analysis.Also, it is the usua l method to analyze the random drift of FOG. The paper studies thewavelet theory, by which analyzing the FOG random drift. Besides, the papercompares the results of the two filter methods with the Allan varia nce. The resultsshow that the wavelet filter method don't need the statistica l test and the datapretreatment. Howev er, it can minish the FOG random drift effectively and the effectis better than Kalman filter method.The paper designs an attitude determination system of"FOG + Star sensor"using extended Kalman filter theory for the Earth-oriented three-axis stabilizedsatellite, basing on the quaternion method. The simulation results show the system isfeasible, with a high precision of attitude estimate. It also show minishing the FOGrandom drift can improve the precision of attitude estimate , proving the mea ning ofthe filter of FOG random drift to improve the system precision.