摘要
对多项式模型及灰色模型存在的问题进行了分析,提出用ARIMA时间序列模型对卫星钟差建模并作1天的短期预报。卫星钟差数据的时间序列分析显示,在对钟差数据做二次差分之后,其相关性与滑动平均模型(MA)相符合,由此建立了卫星钟差的ARIMA(0,2,q)预报模型。计算结果表明,基于ARIMA(0,2,q)的预报模型预测精度优于二次多项式及灰色模型。
The methods currently used in satellite clock error forecasting are quadratic polynomial model and grey model. The shortcomings of these models are discussed,and a new ARIMA（0,2 ,q）model is proposed to model and predict the clock error for one day. The analysis of the time series of satellite clock error reveals that the related character of clock error accords with that of moving average model （MA） after differentiation two times. Thus the ARIMA（0,2 ,q） forecasting model is established. The final results by use of the ARIMA（0,2,q）shows that the integral forecasting accuracy of ARIMA （0,2, q） model is better than those of quadratic polynomial model and grey model.
出处
《大地测量与地球动力学》
CSCD
北大核心
2009年第5期116-120,共5页
Journal of Geodesy and Geodynamics
基金
国家自然科学基金(40774001
40841021)
国家"863"计划项目(2007AA12Z331)
