Time Series Analysis And Prediction Of Geocenter Motion Based On GPS Technology

Mass migration of surface water,atmosphere and ocean etc.causes redistribution of the internal mass of the Earth,bringing out the displacement of the Earth's center of mass relative to the origin of the reference frame.Accurately measuring,analyzing and predicting the geocenter motion can not only reflect the changes in the internal mass of the Earth,but also improve the accuracy and stability of reference frame construction with the origin of center of mass of the Earth,further provide technical support for applications such as geodynamics research,satellite navigation and positioning,and so on.The main contents and conclusions of the thesis are as follows:(1)This paper uses the GPS data to calculate the time series of geocenter motion between 2007 and 2017 by the network translation method.The results show that the magnitude of the geocenter motion is millimeter in all three directions,the average values are 0.27mm,-2.75mm and-2.39mm respectively,the internal accuracy is better than 2.5mm,and the external accuracy is better than 5mm.Moreover,the internal and external accuracy of the X and Y directions are better than the Z direction.(2)Utilize EMD(empirical mode decomposition,EMD)and SSA(Singular Spectrum Analysis,SSA)algorithm to remove the high frequency signal confused in the geocenter motion sequence,weakening the influence of noise on the periodic analysis of the geocenter motion time series.The correlation coefficient and energy percentage with the original sequence and signal-to-noise ratio of the sequence after noise reduction also indicate that both EMD and SSA have certain ability to suppress noise,however SSA is more superior.After EMD noise reduction,The contribution rate of all cycle increased by 12.3%,16.7%and 6.3%evenly in the three directions of X,Y and Z.Also,the all cycle contribution rate increased by 12.18%,3.8%and 6.2%evenly after SSA.For the contribution rate of the relatively highest anniversary item,SSA is 3.66%and 0.8%higher than EMD in the X and Z directions,and only 0.5%lower in the Y direction.(3)The time series of EMD and SSA noise reduction are analyzed by power spectrum and least squares analysis respectively,and the periodic term of geocentric motion is obtained.The annual amplitudes of the EMD denoising time series in three directions are:2.32mm,1.89mm and 2.07mnmi,respectively.The about half year amplitudes are 0.3mm.0.28mm and 0.46mm respectively,and the trend item changes are:-0.02mm/y,0.13 mm/y and-0.27mm/y.The annual amplitude of the time series after SSA noise reduction is 2.30imm,1.91mm and 2.09mm,respectively,and the long-term motion trends are-0.02mm/y,0.13mm/y and-0.25mm/y,respectively.The amplitudes of the annual items directly detected by SSA are 2.27mm,1.84mm and 2.13mm,respectively,and the half year amplitudes are 0.1mm,0.20mm and 0.15mm respectively.In addition,some other interannual variations with relatively small contribution rates have been identified.(4)The ARMA(Auto Regression Moving Average,ARMA)and SSA+ARMA algorithms are used to predict the geocenter motion in short,medium and long term.In the short-term prediction,the accuracy of the two methods is equivalent,and the prediction accuracy of millimeters can be achieved,but SSA+ARMA is more stable.The SSA+ARMA algorithm is more superior on the medium and long-term scale,providing a medium-term prediction accuracy of 1 mm and a long-term prediction accuracy of 1.5 mm.