Middle- and Long-Term UT1-UTC Prediction Based on Constrained Polynomial Curve Fitting, Weighted Least Squares and Autoregressive Combination Model

Universal time (UT1-UTC) is a key component of Earth orientation parameters (EOP), which important for the study monitoring changes in Earth’s rotation rate, climatic variation, and characteristics Earth. Many existing UT1-UTC prediction models are based on combination least squares (LS) stochastic such as Autoregressive (AR) model. However, due to complex periodic series, LS fitting produces large residuals edge distortion, affecting extrapolation accuracy thus accuracy. In this study, we propose combined model polynomial curve (PCF), weighted (WLS), AR, namely, PCF+WLS+AR The PCF algorithm used obtain accurate values, then predicted by WLS+AR To more results, annual interval constraints introduced work determine optimal degree PCF. Finally, multiple sets experiments International Rotation Reference Systems Service (IERS) EOP 14C04 series carried out. comparison results indicate that constrained can efficiently precisely predict mid long term. Compared Bulletin A, proposed improve up 33.2% mid- long-term prediction.