Polar motion prediction using the combination of SSA and ARMA

Abstract

High-precision polar motion (PM) prediction is of important significance in astronomy, geodesy, aviation, hydrographic mapping, interstellar navigation, and so on. SSA can effectively extract the trend and period terms of PM,in the process of achieving high-precision medium- and long-term polar motion prediction, it is necessary to solve the end effect problem and overfitting problem of SSA forecasting method; therefore, ARMA was applied to decreasethe end effect, and a suitable combination of reconstructed components was determined to avoid the high variance reaction of SSA overfitting. Based on the decomposition and reconstruction of the PM by SSA, the reconstructed components are determined to participate in the SSA iterative fitting model according to the variance contribution rate. The combination of the reconstructed components representing the polar motion period term and the trend term is determined according to the correlation analysis of the selected reconstructed components. After the above work, the principal component prediction sequence is obtained by fitting the period term and the trend term to convergence, respectively, and then, the SSA end effect is modified, and the residual term is predicted based on ARMA. The test results show that he prediction accuracy of SSA + ARMA at the front of the X and Y directions are improved by 96.90% and 97.53% compared with those of SSA, respectively, and the forecast accuracy of 365 days are improved by 37.93% and 19.53% in the X and Y directions compared with those of Bulletin A, respectively.