Abstract
This study employs a combination of weighted least-squares extrapolation and an autoregressive model to produce medium-term predictions of polar motion (PM) parameters. The precisions of PM parameters extracted from earth orientation parameter (EOP) products are applied to determine the weight matrix. This study employs the EOP products released by the analysis center of the ‘International Global Navigation Satellite System Service and International Earth Rotation and Reference Systems Service’ needs to be modified to ‘International Global Navigation Satellite System Service (IGS) and International Earth Rotation and Reference Systems Service (IERS)’ as primary data. The polar motion parameters and their precisions are extracted from the EOP products to predict the changes in polar motion over spans of 1–360 days. Compared with the combination of least-squares and autoregressive model, this method shows considerable improvement in the prediction of PM parameters.
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Acknowledgements
The work is supported by the Ordinary University Graduate Student Research Innovation Project of Jiangsu Province (KYLX16_0541), National Natural Science Foundation of China (41774005), National Natural Science Foundation of China (41404033), Open research fund projects of the state key laboratory (SKLGIE2014-Z-1-1) and Project on Basic Research of The National Department of Science and Technology (2015FY310200). We thank the IERS and IIGS for providing the EOPs products.
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Wu, F., Deng, K., Chang, G. et al. The application of a combination of weighted least-squares and autoregressive methods in predictions of polar motion parameters. Acta Geod Geophys 53, 247–257 (2018). https://doi.org/10.1007/s40328-018-0214-3
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DOI: https://doi.org/10.1007/s40328-018-0214-3