摘要
基于自回归滑动平均(auto-regressive and moving average,ARMA)模型以及一阶差分ARMA模型分别对极移的X分量和Y分量进行了模型拟合,并利用所拟合的模型对极移进行了预测。通过与国际地球自转服务发布的实测极移数据以及其他方法对比,证明了所建立的拟合模型在短期预报上的有效性。且X分量的ARMA模型在39d预报跨度内的整体精度优于一阶差分ARMA模型,而Y分量45d内的一阶差分ARMA模型预报精度比ARMA模型预报精度更高。
Based on the ARMA(auto-regressive and moving average)model and the single differential ARMA model,the X and Y components of the polar motion are fitted respectively,and the polar motion is predicted by the fitted model.By comparing with the measured polar motion data released by the International Earth Rotation Service and other methods,the validity of the fitting model in short-term prediction is proved.Moreover,the overall accuracy of the X-component ARMA model is better than that of the single differential ARMA model in the 39days prediction,while the single differential ARMA model in the 45days Y-component has higher prediction accuracy than that of the ARMA model.
作者
张林杰
刘晖
舒宝
杨志鑫
ZHANG Linjie;LIU Hui;SHU Bao;YANG Zhixin(GNSS Research Center,Wuhan University,Wuhan 430079,China)
出处
《测绘地理信息》
CSCD
2021年第4期40-43,共4页
Journal of Geomatics
基金
国家重点研发计划(2016YFB0800405)
武汉市应用基础研究计划(2018010401011271)。
关键词
时间序列
模型拟合
自回归滑动平均模型
一阶差分
极移预报
time series
model fitting
ARMA(auto-regressive and moving average)model
single differential
polar motion prediction
