Objectives In order to find a high accuracy method for satellite clock bias prediction, a preprocessing strategy for wavelet threshold method based on the median absolute deviation(MAD) is proposed to preprocess the small magnitude error of satellite clock bias data.
Methods Firstly, the wavelet threshold method is used to decompose the SCB data to obtain the decomposed high frequency coefficient and low frequency coefficient.Then the MAD method is used to deal with the high frequency coefficient of each layer affecting the threshold setting, and the processed high frequency coefficient is used to calculate the threshold, so as to improve the ability of eliminating small outliers by the wavelet threshold method. Finally, the clock bias data of BeiDou-2 satellite are used to verify.
Results The experimental results show that after modeling the clock bias data processed by the proposed method, the prediction accuracy of wavelet neural network(WNN) model is improved by about 14.1% and the prediction stability is improved by about 19.7%.
Conclusions This method can effectively eliminate the small error in the historical observation sequence of clock bias, improve the quality of clock bias data and the effect of model clock bias prediction.