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.

中文翻译：

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动量轮速数据的建模与预测

为解决卫星稳定运行中数据丢失和动量轮速度间隔不相等的问题，提出了一种多维AR模型。采用拉格朗日插值法将测量值转换为等间隔数据，并采用FFT算法计算兆瓦级速度变化的周期。根据等间隔数据和周期，将长数据序列转换为多维时间序列。建立了多维AR模型，并采用最小二乘法估计模型参数。所提出的模型可以预测未来的数据趋势。仿真结果表明，该预测算法可以实现兆瓦级速度数据的跨周期预测。