提出基于双差分最小二乘LS+AR模型的高精度极移参数预报方法。首先，对极移数据进行双差分处理，用以增强数据平稳性，获取差分极移数据，并采用LS方法对差分极移数据进行拟合，获取极移残差数据|其次，利用AR模型对极移残差数据进行预报|然后，综合LS外推预报值与AR模型预报值获取差分极移预报值|最后，对差分极移预报结果进行逆双差分处理，获取高精度的极移预报值。将该方法应用于实际极移参数预报中，结果表明，1 d的极移X分量（PMX）预报精度优于0.25 mas，极移Y分量(PMY)预报精度优于0.2 mas。将该预报结果与国际EOP_PCC预报结果对比表明，极移短期预报精度与EOP_PCC预报结果相当，1 d 的预报精度略优于EOP_PCC预报结果。

This paper proposes a high accuracy prediction method for Earth polar motion parameters, using a dual differential least-squares (LS) and autoregressive (AR) model.  Firstly, Earth polar motion parameters are calculated by dual differential methods to obtain differential results.  The stationarity of differential polar motion parameters is improved.  The LS method is utilized to fit the differential polar motion parameters to obtain the residual results.  Secondly, the AR model is utilized to analyze the residual polar motion parameters.  Thirdly, the extrapolated results of LS and AR model prediction results are combined to obtain the differential prediction results.  Finally, the differential prediction results are calculated by inverse dual differential methods, to obtain the final prediction results.  The proposed method is applied to the real Earth polar motion parameters prediction.  The results show that 1 day’s PMX prediction accuracy is better than 0.25 mas, and 1 day’s PMY prediction accuracy is better than 0.2 mas.  These results are compared with EOP_PCC results.  It shows that this paper’s polar motion parameters short term prediction accuracy is close to EOP_PCC good prediction accuracy, and that 1 day’s prediction accuracy is a little better than EOP_PCC 1 day’s prediction accuracy.