摘要
提出采用多元回归模型(MAR)与最小二乘(LS)组合进行极移预报。该模型考虑极移PMX和PMY的LS拟合残差之间的相关性,采用PMX残差和PMY残差一起构建预报模型进行残差预报。通过与LS+AR预报结果的对比表明,LS+MAR模型的预报结果更优。此外,通过与EOP_PCC预报结果的对比也说明,LS+MAR模型的短期极移预报精度能够达到国际先进水平。
The multivariable regression model combined with least squares is proposed to forecast polar motion.The residual error prediction model is constructed by using the PMX residual and PMY residuals,which not only utilizes the correlation information of the PMX residual and the PMY residual,but also uses the correlation information between the PMX residual and the PMY residual.By comparison with the prediction results of LS＋AR model,it is proven that the prediction result of LS＋MAR model is better than that of LS＋AR model,and the superiority of LS＋ MAR model is also proven.In addition,by comparison with the prediction results of EOP_PCC,it is proven that the LS＋MAR model can obtain the prediction results equivalent to the best international prediction accuracy in short-term polar motion prediction.
作者
王志文
王潜心
何义磊
胡超
WANG Zhiwen WANG Qianxin HE Yilei HU Chao(School of Environment Science and Spatial Informatics, China University of Mining and Technology, 1 Daxue Road, Xuzhou 221116, China)
出处
《大地测量与地球动力学》
CSCD
北大核心
2017年第11期1178-1182,共5页
Journal of Geodesy and Geodynamics
基金
国家自然科学基金(41404033)
国家科技部科技基础性工作专项(2015FY310200)~~
