College of Geodesy and Geomatics, Shandong University of Science and Technology, Qingdao 266590, China.
State Key Laboratory of Mining Disaster Prevention and Control Co-Founded by Shandong Province and Ministry of Science and Technology, Shandong University of Science and Technology, Qingdao 266590, China.
Sensors (Basel). 2020 May 16;20(10):2823. doi: 10.3390/s20102823.
Polar motion (PM) has a close relation to the Earth's structure and composition, seasonal changes of the atmosphere and oceans, storage of waters, etc. As one of the four major space geodetic techniques, doppler orbitography and radiopositioning integrated by satellite (DORIS) is a mature technique that can monitor PM through precise ground station positioning. There are few articles that have analyzed the PM series derived by the DORIS solution in detail. The aim of this research was to assess the PM time-series based on the DORIS solution, to better capture the time-series. In this paper, Fourier fast transform (FFT) and singular spectrum analysis (SSA) were applied to analyze the 25 years of PM time-series solved by DORIS observation from January 1993 to January 2018, then accurately separate the trend terms and periodic signals, and finally precisely reconstruct the main components. To evaluate the PM time-series derived from DORIS, they were compared with those obtained from EOP 14 C04 (IAU2000). The results showed that the RMSs of the differences in PM between them were 1.594 mas and 1.465 mas in the X and Y directions, respectively. Spectrum analysis using FFT showed that the period of annual wobble was 0.998 years and that of the Chandler wobble was 1.181 years. During the SSA process, after singular value decomposition (SVD), the time-series was reconstructed using the eigenvalues and corresponding eigenvectors, and the results indicated that the trend term, annual wobble, and Chandler wobble components were accurately decomposed and reconstructed, and the component reconstruction results had a precision of 3.858 and 2.387 mas in the X and Y directions, respectively. In addition, the tests also gave reasonable explanations of the phenomena of peaks of differences between the PM parameters derived from DORIS and EOP 14 C04, trend terms, the Chandler wobble, and other signals detected by the SSA and FFT. This research will help the assessment and explanation of PM time-series and will offer a good method for the prediction of pole shifts.
极移（PM）与地球的结构和组成、大气和海洋的季节性变化、水的储存等密切相关。作为四大空间大地测量技术之一，卫星多普勒轨道制图和无线电定位综合技术（DORIS）是一种成熟的技术，可以通过精确的地面站定位监测 PM。很少有文章详细分析 DORIS 解算得到的 PM 序列。本研究旨在评估基于 DORIS 解算的 PM 时间序列，以更好地捕捉时间序列。本文应用傅里叶快速变换（FFT）和奇异谱分析（SSA）分析了 1993 年 1 月至 2018 年 1 月 DORIS 观测解算的 25 年 PM 时间序列，准确分离趋势项和周期信号，最后精确重建主要成分。为了评估 DORIS 解算得到的 PM 时间序列，将其与 EOP14C04（IAU2000）得到的 PM 时间序列进行比较。结果表明，X、Y 方向 PM 差值的 RMS 分别为 1.594mas 和 1.465mas。FFT 谱分析表明，年度摆动的周期为 0.998 年，钱德勒摆动的周期为 1.181 年。在 SSA 过程中，经过奇异值分解（SVD）后，使用特征值和相应的特征向量对时间序列进行重建，结果表明趋势项、年度摆动和钱德勒摆动分量得到了准确分解和重建，重建结果的精度在 X、Y 方向上分别为 3.858mas 和 2.387mas。此外，测试还对 DORIS 和 EOP14C04 解算得到的 PM 参数差值的峰值、趋势项、钱德勒摆动等信号的 SSA 和 FFT 检测结果给出了合理的解释。本研究将有助于 PM 时间序列的评估和解释，并为极移预测提供良好的方法。
