摘要
以美国德克萨斯大学空间研究中心提供的地心运动时间序列为实验数据,首先采用经验模态分解(empirical mode decomposition,EMD)对数据进行降噪处理;然后利用快速傅里叶变换(fast Fourier transform,FFT)和连续小波变换(continuous wavelet transform,CWT)对该数据进行频域转换、功率谱分析和周期项提取;最后采用自回归积分滑动平均(autoregressive integrated moving average,ARIMA)模型和指数平滑法对未来20个月的地心运动进行预报。结果表明,利用FFT提取的周年项的振幅和相位与以往的地心运动研究较为接近;ARIMA模型对于Y方向20个月内的地心运动预测结果较好,指数平滑法对X、Z方向的地心运动预测结果更优。
This paper uses the time series of the geocentric motion provided by the Center for Space Research at the University of Texas at Austin as experimental data.First,empirical mode decomposition(EMD)is applied to the data for noise reduction.Then,fast Fourier transform(FFT)and continuous wavelet transform(CWT)are utilized to perform frequency domain transformation,power spectrum analysis,and extraction of periodic terms.Finally,an autoregressive integrated moving average(ARIMA)model and exponential smoothing method are employed to forecast the geocentric motion for the next 20 months.The results indicate that the amplitude and phase of the annual term extracted using FFT are quite close to previous studies on the geocentric motion.The ARIMA model provides better predictions for the Y-direction motion of the geocentric motion over the next 20 months,while exponential smoothing method offers more accurate predictions for the X and Z directions.
作者
魏二虎
吴俊杰
张云龙
罗一乐
邹贤才
田晓静
刘经南
WEI Erhu;WU Junjie;ZHANG Yunlong;LUO Yile;ZOU Xiancai;TIAN Xiaojing;LIU Jingnan(School of Geodesy and Geomatics,Wuhan University,129 Luoyu Road,Wuhan 430079,China;China Railway Design Corporation,10 Minjiang Road,Tianjin 300251,China;Geodetic Data Processing Center,MNR,334 East-Youyi Road,Xi’an 710054,China;GNSS Research Center,Wuhan University,129 Luoyu Road,Wuhan 430079,China)
出处
《大地测量与地球动力学》
北大核心
2025年第4期331-338,共8页
Journal of Geodesy and Geodynamics
基金
国家自然科学基金(42374015)
国家重点研发计划(2018YFC1503600)
天津市轨道交通导航定位及时空大数据技术重点实验室开放基金(TKL2024B04)。
关键词
地心运动
快速傅里叶变换
连续小波变换
ARIMA
指数平滑法
geocentric motion
fast Fourier transform
continuous wavelet transform
ARIMA
exponential smoothing method
