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The application of a combination of weighted least-squares and autoregressive methods in predictions of polar motion parameters

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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… Click to show full 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.

Keywords: motion parameters; motion; least squares; polar motion; combination weighted

Journal Title: Acta Geodaetica et Geophysica
Year Published: 2018

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