极地运动(PM)与地球的结构和组成密切相关,大气和海洋的季节性变化,储存水,等。作为四大空间大地测量技术之一,卫星多普勒轨道成像和无线电定位(DORIS)是一种成熟的技术,可以通过精确的地面站定位来监测PM。很少有文章详细分析了DORIS解决方案派生的PM系列。这项研究的目的是评估基于DORIS解决方案的PM时间序列,更好地捕捉时间序列。在本文中,应用傅里叶快速变换(FFT)和奇异谱分析(SSA)分析了从1993年1月到2018年1月由DORIS观测解决的25年PM时间序列,然后准确地分离出趋势项和周期信号。最后精确地重建了主要组件。要评估从DORIS导出的PM时间序列,将它们与从EOP14C04(IAU2000)获得的进行比较。结果表明,它们在X和Y方向上的PM差异的RMS分别为1.594mas和1.465mas,分别。使用FFT进行的频谱分析表明,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),使用特征值和相应的特征向量重建时间序列,结果表明,趋势项,每年的摇摆,钱德勒摆动分量被精确地分解和重建,分量重建结果在X和Y方向的精度分别为3.858和2.387mas,分别。此外,测试还对DORIS和EOP14C04得出的PM参数之间的差异峰值现象进行了合理的解释,钱德勒的摇摆,以及由SSA和FFT检测到的其他信号。这项研究将有助于评估和解释PM时间序列,并将为极移的预测提供一个很好的方法。
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.