Abstract: To improve the accuracy in medium-term and long-term prediction of a single satellite clock bias prediction model when the amount of modeling data is small, a combined prediction model based on grey model and first-order difference modified exponential curve method is proposed. In the model, a small amount of historical clock data is used to build a grey model and predict the clock data in the future, and then the prediction data is used as the modeling data of the first order difference modified exponential curve model to make the medium-term and long-term prediction of the clock. The simulation results show that the combined prediction model can forecast the clock difference with high accuracy based on a small amount of historical data. The experiment is carried out based on the precise clock difference data collected by the satellite common view instrument. Compared with the single quadratic polynomial model and the gray model, the results show that when using 5h clock difference data for modeling and forecasting 48h clock difference data in the future, the average prediction accuracy of quadratic polynomial model and gray model is 285.06ns and 91.11ns, respectively, while the average prediction accuracy of combined model is 29.48ns. Thus, compared with the single quadratic polynomial model and gray model, the proposed combined prediction model achieves 89.66% and 67.64% accuracies gains, respectively.

Key words: satellite clock bias prediction, grey model, composite model