张旺,尹磊,徐韶光,熊永良

• 1:国网四川省电力公司经济技术研究院
• 2:西南交通大学地球科学与环境工程学院

摘要(Abstract)：

针对传统奇异谱分析方法具有相移现象缺点而不能有效分析,是由于不同形式的地球物理现象而包含有阶跃项、非线性趋势项、以及振幅随时间变化的季节项,从而呈现显著的非线性变化的时间序列,该文提出了一种用于拟合GPS时间序列的改进奇异谱分析方法。采用实际IGS站点数据将改进奇异谱分析方法与小波分析方法进行比较,结果表明,改进奇异谱分析方法在提取年以及半年季节项要优于小波分析方法。基于模拟数据计算表明:模拟信号和改进奇异谱分析方法重构信号残差的均方根小于1.8mm,改进奇异谱分析方法拟合精度显著优于传统奇异谱分析方法。改进奇异谱分析方法消除了传统奇异谱分析方法具有相移现象缺点。

关键词(KeyWords)： GPS时间序列;奇异谱分析方法;小波分析方法;相移现象;功率谱

Abstract:

Keywords:

基金项目(Foundation): 国家自然科学基金项目(41674028)

作者(Author): 张旺,尹磊,徐韶光,熊永良

DOI: 10.16251/j.cnki.1009-2307.2019.03.005

参考文献(References)：

• [1]姜卫平,李昭,刘鸿飞,等.中国区域IGS基准站坐标时间序列非线性变化的成因分析[J].地球物理学报,2013,56(7):2228-2237.(JANG Weiping,LI Zhao,LIU Hongfeng,et al.Cause analysis of the non-linearvariation of the IGS reference station coordinate timeseries in-side China[J].Chinese Journal of Geophysics,2013,56(7):2228-2237.
• [2]ALTAMIMI Z,METIVIER L,COLLILIEUX X.ITRF2008plate motion model[C]∥AGU Fall Meeting.[S.l.]:AGU Fall Meeting Abstracts,2011:47-56.
• [3]AITAMIMI Z,REBISCHUNG P,METIVIER L,et al.ITRF2014:a new release of the internationalterrestrial reference frame modeling non-linear stationmotions[J].Journal of Geophysical Research SolidEarth,2016,121(8):6109-6131.
• [4]GAZEAUX J,WILLIAMS S,KING M,et al.Detectingoffsets in GPS time series:first results from thedetection of offsets in GPS experiment[J].Journal ofGeophysical Research Solid Earth,2013,118(5):2397-2407.
• [5]HACKL M,MALSERVISI R,HUGENTOBLER U,et al.Velocity covariance in the presence of anisotropictime correlated noise and transient events in GPS timeseries[J].Journal of Geodynamics,2013,72(12):36-45.
• [6]袁林果,丁晓利,陈武,等.香港GPS基准站坐标序列特征分析[J].地球物理学报,2008,51(5):418-420.(YUAN Linguo,DING Xiaoli,CHEN Wu,et al.Characteristics of daily position time series from theHong Kong GPS fiducial network[J].Chinese Journalof Geophysics,2008,51(5):418-420.
• [7]李昭,姜卫平,刘鸿飞,等.中国区域IGS基准站坐标时间序列噪声模型建立与分析[J].测绘学报,2012,41(4):496-503.(LI Zhao,JIANG Weiping,LIU Hong-fei,et al.Noise model establishment and analysis ofIGS reference station coordinate time series insideChina[J].Acta Godaetica et Cartographica Sinica,2012,41(4):496-503.)
• [8]明锋,杨元喜,曾安敏,等.中国区域IGS站高程时间序列季节性信号及长期趋势分析[J].中国科学(地球科学),2016,46(6):834.(MING Feng,YANG Yuanxi,ZENG Anmin,et al.Analysis of seasonal signals and long-term trends in the height time series of IGS sites in China[J].Science China Earth Sciences,2016,46(6):834.)
• [9]BENNETT R A.Instantaneous deformation fromcontinuous GPS:contributions from quasi-periodicloads[J].Geophysical Journal of the Royal AstronomicalSociety,2010,174(3):1052-1064.
• [10]DAVIS J L,WERNICKE B P,TAMISIEA M E.Onseasonal signals in geodetic time series[J].Journal ofGeophysical Research Solid Earth,2012,117:B01403.
• [11]CHEN Q,DAM T V,SNEEUWN,et al.Singularspectrum analysis for modeling seasonal signals fromGPS time series[J].Journal of Geodynamics,2013,72(12):25-35.
• [12]VAUTARD R,YIOU P,GHIL M.Singular-spectrumanalysis:A toolkit for short,noisy chaotic signals[J].Physica D-nonlinear Phenomena,1992,58(1/4):95-126.
• [13]RANGELOVA E,SIDERIS M G,KIM J W.On thecapabilities of the multi-channel singular spectrummethod for extracting the main periodic and non-periodicvariability from weekly GRACE data[J].Journal ofGeodynamics,2012,54(2):64-78.
• [14]REA W,OXLEY L,REALE M,et al.Estimators forlong range dependence:an empirical study[J].Statistics,2009,3(4):785-798.
• [15]VAUTARD R,YIOU P,GHIL M.Singular-spectrumanalysis:a toolkit for short,noisy chaotic signals[J].Physica D-nonlinear Phenomena,1992,58(1/4):95-126.
• [16]TREGONING P,BURGETTE R,MCCLUSKY S C,et al.A decade of horizontal deformation from greatearthquakes[J].Journal of Geophysical Research SolidEarth,2013,118(5):2371-2381.
• [17]韩英,符养.GPS高程数据时间序列分析[J].武汉大学学报(信息科学版),2003,28(4):425-428.(HANGYing,FU Yang.Analysis of GPS time series of heightcomponent[J].Geomatics and Information Science ofWuhan University,2003,28(4):425-428.)
• [18]RAY J,ALTAMIMI Z,COLLILIEUX X,et al.Anomalous harmonics in the spectra of GPS positionestimates[J].GPS Solutions,2008,12(1):55-64.
• [19]HE X,HUA X,YU K,et al.Accuracy enhancement ofGPS time series using principal component analysis andblock spatial filtering[J].Advances in Space Research,2015,55(5):1316-1327.