| 利用奇异谱分析提高极移中长期预报精度 |
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| 引用本文： | 赵丹宁,雷雨,乔海花.利用奇异谱分析提高极移中长期预报精度[J].天文学报,2024,65(3):24. |
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| 作者姓名： | 赵丹宁 雷雨 乔海花 |
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| 作者单位： | 宝鸡文理学院电子电气工程学院 宝鸡 721016;西安邮电大学计算机学院 西安 710121;中国科学院国家授时中心 西安 710600 |
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| 基金项目： | 国家自然科学基金项目(11503031), 陕西省自然科学基础研究计划(2022-JM031、2023-JC-YB-057)和中国科学院青年创新促进会项目资助 |
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| 摘 要： | 由于空间大地观测数据传输耗时及处理过程复杂, 导致极移测量值的获取存在时延, 无法满足对高精度的极移预报值有重大需求的应用领域. 针对极移复杂的时变特性, 提出一种基于奇异谱分析(singular spectrum analysis, SSA)的预报方法. 首先用SSA分离提取极移时序中的高频组分与低频组分; 其次建立最小二乘(least square, LS)外推与自回归(AutoreGressive, AR)模型对极移高频和低频组分进行组合预报. 结果表明, SSA方法能够准确地分离和提取极移低频和高频组分, 对低频和高频组分组合预报可以显著改善极移的中长期(30--365d)预报精度, 与国际地球自转和参考系服务局(International Earth Rotation and Reference Systems Service, IERS)提供的A公报中的极移预报值相比, SSA方法对极移PMX分量(本初子午线方向)和PMY分量(西90$^\circ$子午线方向)的中长期预报精度改进最高分别可达45.97%和62.44%. 研究结果验证了SSA方法对极移中长期预报改进的有效性.
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| 关 键 词： | 天体测量学: 参考系 地球自转: 极移 方法: 数据分析 |
| 收稿时间： | 2023/1/3 0:00:00 |
Improvement in the Medium- and Long-term Prediction Accuracy of Polar Motion Using Singular Spectrum Analysis |
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| ZHAO Dan-ning,LEI Yu,QIAO Hai-hua.Improvement in the Medium- and Long-term Prediction Accuracy of Polar Motion Using Singular Spectrum Analysis[J].Acta Astronomica Sinica,2024,65(3):24. |
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| Authors: | ZHAO Dan-ning LEI Yu QIAO Hai-hua |
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| Institution: | School of Electrical and Electronic Engineering, Baoji University of Arts and Sciences, Baoji 721016;School of Computer Science and Technology, Xián University of Posts and Telecommunications, Xián 710121; National Time Service Center, Chinese Academy of Sciences, Xián 710600 |
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| Abstract: | Polar motion cannot be determined in real time owing to the delay caused by data transfer and heavy computation procedures. Polar motion predictions are therefore required for many real-time applications and geodynamics study. Polar motion with respect to the axis of the terrestrial reference system is not constant in time but changes due to external forces and internal processes. This paper proposes a hybrid method to improve polar motion prediction based on singular spectrum analysis (SSA). In this method, the SSA is employed to separate and extract the low- and high-frequency components of polar motion. Next, the least square (LS) extrapolation and autoregressive (AR) models are applied to model and predict the extracted low- and high-frequency components, respectively. The subsequent predictions of the low- and high-frequency components are summed to obtain the predicted values of polar motion. The singular spectrum analysis of the polar motion time-series shows that the low- and high-frequency components can be accurately extracted from the original time-series of polar motion by the SSA technology. Further, the prediction results illustrate that the proposed SSA-based combined model can substantially improve the medium- and long-term predictions of polar motion out 30days in the future. In comparison with the polar motion predictions from the Bulletin A published by the International Earth Rotation and Reference Systems Service (IERS), the highest improvements found for PMX in the prime meridian direction and PMY in the west 90$^\circ$ meridian direction are 45.97% and 62.44% up to 365 days in the future, respectively. It is concluded that the SSA is a potential method to enhance medium- and long-term predictions of polar motion. |
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| Keywords: | astrometry: reference systems Earth rotation: polar motion methods: data analysis |
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