基于ARMA模型的导航卫星钟差长期预报

Long-term Satellite Clock Bias Prediction Based on ARMA Model

卫星钟差长期可靠预报是实现卫星自主导航定轨所要解决的重要前提之一.针对多项式模型(PM)、灰色模型(GM)等常用的钟差预报方法存在的预报误差较大的情况,为了有效地进行卫星钟差预报和更好地反映卫星钟差变化特性,将ARMA(Auto-Regressive Moving Average)模型引入到卫星钟差预报中,利用IGS(International GNSS Service)提供的卫星钟差观测数据进行90 d的长期预报,根据各个卫星钟差的变化特性,对其进行模式识别、建模和预报,并与其它3种模型进行了较为细致的比较.计算结果表明,采用ARMA模型可以有效地提高卫星钟差的长期预报精度.

The long-term and reliable prediction of satellite clock bias （SCB） is a key to implement the satellite autonomous navigation and orbit determination. Considering the shortcomings of the quadratic polynomial model （PM） and gray system model （GM） in predicting the long-term SCB, a new prediction method of SCB that based on the ARMA （Auto-Regressive Moving Average） model is proposed to predict SCB, and show its property clearer. In this paper, a careful precision analysis of the 90-day SCB prediction is made to verify the feasibility and validity of this proposed method by using the IGS （International GNSS Service） clock data. According to the various changes of each satellite clock, the pattern recognition, modeling, and predicting are conducted, and the detailed comparison is made with the other three models at the same time. The results show that the ARMA model is reliable and valid to predict the long-term SCB.