| 一种考虑PMX与PMY之间相关性的极移预报新方法 |
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| 引用本文： | 王志文,王潜心,何义磊,胡 超.一种考虑PMX与PMY之间相关性的极移预报新方法[J].大地测量与地球动力学,2017,37(11):1178-1182. |
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| 作者姓名： | 王志文 王潜心 何义磊 胡 超 |
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| 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。
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| 关 键 词： | LS模型 AR模型 MAR模型 极移预报 |
A New Method to Predict Pole Shift Based on the Correlation Between PMX and PMY |
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| WANG Zhiwen,WANG Qianxin,HE Yilei,HU Chao.A New Method to Predict Pole Shift Based on the Correlation Between PMX and PMY[J].Journal of Geodesy and Geodynamics,2017,37(11):1178-1182. |
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| Authors: | WANG Zhiwen WANG Qianxin HE Yilei HU Chao |
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| Abstract: | 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. |
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| Keywords: | LS model AR model MAR model polar motion prediction |
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