Modeling and Prediction of Momentum Wheel Speed Data

To solve the problems of data loss and unequal interval of momentum wheel (MW) speed during a satellite stable operation, this paper presents a multidimensional AR model. A Lagrange interpolation method is used to convert measurements to equal interval data, and the FFT algorithm is adopted to calculate the period of MW speed variation. The long data sequence is converted into multidimensional time series, based on the equal interval data and the period. A multidimensional AR model is established, and the least square method is used to estimate the model parameters. The future data trend is predicted by the proposed model. Simulation results show that the prediction algorithm can achieve the across cycle prediction of the MW speed data