Research on Polar Motion Prediction Considering Basic Data Volume of LS+AR Model

Based on the single data input method of the current LS (Least Square) + AR (AutoRegressive) model of polar motion forecasting, this paper considers a combined data mode of the sequence length of the LS model and the AR residual data separately. The single data and the combined data are respectively used for forecasting, and then the forecast accuracy is analyzed, and the influence of the model input data volume on the accuracy of the polar motion forecast is discussed. The results show that the change in the amount of input data of the model has a greater impact on the prediction results of polar motion. The combined data forecasting method has higher accuracy than the single data, especially for the medium and long-term forecasts within a span of 30 to 360 days. The combined data forecast accuracy can be greatly improved compared to the single data forecasting accuracy. The conclusion proves that the combined data has certain advantages in the prediction of polar motion, and it can provide a certain reference for the selection of data volume of polar motion forecast in the future.