BD/GPS卫星钟差短期预报模型分析

Model Analysis on Short-term Prediction of Satellite Clock Bias

采用GNSS数据中心提供GPS/BDS钟差数据作为实验数据,对二次多项式模型(the Quadratic PolynoMial(QP)model)、灰色模型(the Gray system Model(GM(1,1)))、时间序列模型(the ARIMA time series model)、卡尔曼滤波模型(KF)、小波神经网络模型(Wavelet Neural Network(WNN))五种模型钟差短期预报的效果进行分析和比较,总结了各模型预报钟差的优点与不足。

In order to analyze the performance of several methods used for navigation atellite clock bias prediction,the paper uses the precise SCB data provided by GNSS data center to analyze the prediction accuracy of the quadratic polynomial model(QP),grey system(GM(1,1))model,time series model(ARIMA model),as well as wavelet neural network(WNN),The advantages and disadvantages of these methods are finally compared.