Abstract In order to improve satellite clock bias prediction, a new prediction method is proposed considering periodic errors and stochastic characteristics. First, the given satellite clock bias is fitted by four quadratic polynomial models with one to four dominating periodic errors; the best model is then chosen to obtain the fitting residuals. Then, the prediction of the fitting residuals is modeled based on grey model, considering the stochastic characteristics of the fitting residuals. Finally, the clock bias based on the best of the four models and prediction of the fitting residuals are combined to obtain the ultimate prediction result. The precise data of satellite clock bias within 15 min from IGS are used to conduct experiments on different models. The results show that the model with two dominating periodic errors is better than the model with other dominating periodic errors and that the proposed model performs better than commonly used models in short-term prediction.
SUN Dashuang,LU Zhiping,WANG Yupu et al. A Method of Satellite Clock Bias Prediction Considering Periodic Errors and Stochastic Characteristics[J]. jgg, 2016, 36(12): 1078-1082.
SUN Dashuang,LU Zhiping,WANG Yupu et al. A Method of Satellite Clock Bias Prediction Considering Periodic Errors and Stochastic Characteristics[J]. jgg, 2016, 36(12): 1078-1082.