Comparison and Precision Analysis of Several BDS Satellite Clock Bias Prediction Algorithms

In order to analyze the influence of different data amounts on the accuracy and stability of BDS satellite clock bias prediction model, BDS satellites of different systems were randomly selected in this paper, and post-event precision satellite clock bias data released by Wuhan University was used. The prediction accuracy and stability of quadratic polynomial model, grey prediction model and autoregressive moving average model are compared and analyzed in detail by using different modelling schemes. The experimental results show that the prediction accuracy and stability of quadratic polynomial model are the highest, followed by the autoregressive moving average model and the grey prediction model, and the quadratic polynomial model and the autoregressive moving average model are more sensitive to the amount of data involved in modelling. In addition, the autoregressive moving average model has the highest prediction accuracy and stability for BDS-2 system satellite clock bias, and the grey prediction model has the highest prediction accuracy and stability for BDS-3 system satellite clock bias.