| 利用小波分解改进极移预报模型 |
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| 引用本文： | 赵丹宁,高蕊,雷雨.利用小波分解改进极移预报模型[J].武汉大学学报(信息科学版),2019,44(12):1797-1801. |
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| 作者姓名： | 赵丹宁 高蕊 雷雨 |
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| 作者单位： | 1.宝鸡文理学院电子电气工程学院, 陕西 宝鸡, 721013 |
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| 基金项目： | 国家自然科学基金11503031中国科学院西部之光项目XAB2017B06 |
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| 摘 要： | 为进一步提高极移预报精度，将小波分解引入极移预报中。首先利用小波分解对极移序列进行分解，分离低频分量与高频分量，然后对低频分量建立最小二乘外推模型，获得极移序列的趋势项外推值与残差序列，最后采用自回归（autoregressive，AR）模型对高频分量与残差序列之和进行预报，最终极移的预报值为最小二乘外推值与AR模型预报值之和。结果表明，小波分解可以明显改善最小二乘外推与AR组合模型的极移预报精度，尤其对于中长期预报改善更为明显。
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| 关 键 词： | 极移 预报 小波分解 LS+AR模型 数据预处理 |
| 收稿时间： | 2018-11-17 |
Improvement of the Polar Motion Prediction Model Using Wavelet Decomposition |
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| Institution: | 1.School of Electrical&Electronic Engineering, Baoji University of Arts and Sciences, Baoji 721013, China2.National Time Service Center, Chinese Academy of Sciences, Xi'an 710600, China |
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| Abstract: | In order to further improve the prediction accuracy of polar motion, a wavelet decompositionbased method for polar motion prediction is proposed. In this method, the wavelet decomposition is first used to decompose polar motion time-series into approximation and detailed signals. These approximation and detailed signals are then reconstructed to obtain low- and high-frequency components of polar motion. Furthermore, the least-squares (LS) extrapolation of models for the linear trend, Chandler and annual wobbles are used for predicting low-frequency components, while the autoregressive (AR) model is employed to forecast the high-frequency components together with the residuals derived by subtracting the LS extrapolation curve from the low-frequency components. Finally, polar motion predictions are made by the combination of the LS extrapolation and AR model. The results show that the polar motion predictions can be improved using the proposed wavelet decomposition-based method, especially medium- and long-term predictions. |
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