| 基于PCA方法的GPS台站时间序列分析 |
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| 引用本文： | 张晶,王小亚,胡小工.基于PCA方法的GPS台站时间序列分析[J].大地测量与地球动力学,2019,39(6):613-619. |
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| 作者姓名： | 张晶 王小亚 胡小工 |
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| 作者单位： | 中国科学院上海天文台,上海市南丹路80号,200030;中国科学院大学,北京市玉泉路19号甲,100049;中国科学院上海天文台,上海市南丹路80号,200030 |
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| 基金项目： | 国家科技基础性工作专项;国家重点研发计划;国家自然科学基金;国家自然科学基金 |
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| 摘 要： | 基于10 a以上的全球GPS台站数据，利用主成分分析法及其他数据处理方法，对台站时间序列进行预处理和结果分析，研究其中的非线性周期规律，探讨时间序列的主要影响机制。结果表明，主成分分析法可以将台站残差时空矩阵分解成若干正交成分，GPS台站时间序列的东西方向具有线性漂移趋势，全球大部分GPS台站都存在非线性周期规律，周年项和半周年周期占据主导地位。
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| 关 键 词： | 时间序列 主成分分析 小波变换 GPS |
Analysis of GPS Stations’ Time Series Based on PCA Method |
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| ZHANG Jing,WANG Xiaoya,HU Xiaogong.Analysis of GPS Stations’ Time Series Based on PCA Method[J].Journal of Geodesy and Geodynamics,2019,39(6):613-619. |
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| Authors: | ZHANG Jing WANG Xiaoya HU Xiaogong |
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| Abstract: | Based on more than ten years of global GPS station data, we carry out preprocessing of the detection and reparation of jumps through the wavelet transform, and introduce the PCA method to measure the station time. The feasibility and results of sequence changes are analyzed and evaluated. The most important nonlinear periodic item is extracted from the series. It shows that the principal component analysis method uses the method of orthogonal decomposition and coordinate residual space-time matrix decomposition into a number of orthogonal components. The results reveal that the residual time series shows obvious cyclical terms, and the east direction has a linear drift trend. Through the Fourier transform, the periodic term in the coordinate time series is extracted, showing that most of the global GPS stations have nonlinear periodic laws, in which annual and semi-annual cycles dominate, and the information related to geophysical phenomena is extracted for feature recognition. |
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| Keywords: | time series principal component analysis wavelet transform GPS |
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