Results 251 to 260 of about 14,054 (271)

Autocovariance prediction of complex-valued polar motion time series

Advances in Space Research, 2002
Abstract Autocovariance prediction formulae of complex-valued time series are derived and applied to predict pole coordinate data. The pole coordinate data are transformed into the polar motion radius and angular distance and afterwards their predictions are computed.
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Polar Motion Prediction with Derivative Information

Our study introduces a hybrid model that combines least-squares (LS) extrapolation of a linear trend and periodic components with a vector autoregression applied to LS residuals in an attempt of enhancing polar motion (x, y) predictions through incorporating its rates (derivatives; x', y').
Marcin Ligas, Maciej Michalczak, Santiago Belda, Jose M. Ferrandiz, Sadegh Modiri   +4 more
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Earth Polar Motion Parameters High Accuracy Differential Prediction

2014
This paper proposes a method of Earth polar motion parameters prediction by dual differential least-squares (LS) and autoregressive (AR) model. Firstly, polar motion parameters are processed by dual differential method, the stationarity of polar motion parameters is improved.
Lue Chen, Geshi Tang, Songjie Hu, Ming Chen, Yifei Li, Mei Wang, Jing Sun, Ming Shi, Li Li   +8 more
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Long-term prediction of polar motion using a combined SSA and ARMA model

Journal of Geodesy, 2017
To meet the need for real-time and high-accuracy predictions of polar motion (PM), the singular spectrum analysis (SSA) and the autoregressive moving average (ARMA) model are combined for short- and long-term PM prediction. According to the SSA results for PM and the SSA prediction algorithm, the principal components of PM were predicted by SSA, and ...
Yi Shen, Jinyun Guo, Xin Liu, Qiaoli Kong, Linxi Guo, Wang Li   +5 more
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A Super-Long-Term Prediction Method of Earth Polar Motion Based on Spectrum Analysis

2021
The super-long-term prediction technology of Earth Orientation Parameter (EOP) is a key foundation in autonomous orbit determination for earth-orbit spacecraft. Currently the classical prediction method of EOP is LS + AR, while the accuracy of periodic components and the corresponding frequency of EOP in the LS model is to affect the prediction ...
Weitao Lu, Lue Chen, Zhijin Zhou, Songtao Han, Tianpeng Ren   +4 more
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A Method for Polar Motion Prediction Based on LS Model of Error Compensation

2017
Polar motion is an important component of the Earth Rotation Parameter (ERP). Not only is it one of the necessary transformation parameters between International Celestial Reference Frame (ICRF) and International Terrestrial Reference Frame (ITRF), but it is also essential for deep space exploration mission and satellite ultra-fast precise orbit ...
Zhiwen Wang, Hui Xu, Qianxin Wang, Yilei He   +3 more
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The CNN-LSTM-attention model for short term prediction of the polar motion

Measurement Science and Technology
Abstract The accuracy of polar motion (PM) prediction significantly impacts the fields of coordinate frame transformation, satellite orbit determination, and deep space exploration. The present study develops two short term forecasting models based on the EOP 14C04 series.
Leyang Wang, Haibo Que, Fei Wu
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Polar Motion Prediction by the Least-Squares Collocation Method

1990
In this paper a method of prediction of polar motion for up to 75 days ahead has been proposed. The method is based on least-squares collocation. Two models of the deterministic part of polar motion have been considered. The first numerical results are presented.
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Possible enhancement of Earth’s polar motion predictions using a wavelet-based preprocessing procedure

Studia Geophysica et Geodaetica, 2018
Earth’s polar motion predictions are essential in near real-time applications including spacecraft navigation and satellite orbit determinations and are also important for geophysics studies. It has previously been demonstrated that the basic problem in predicting a polar motion time-series is to treat separately its low- and high-frequency components.
Danning Zhao, Yu Lei
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Optimizing the Input of Liouville Convolution Improves the 10 Day Predictions of Polar Motion

Research in Astronomy and Astrophysics
Abstract This study addresses the critical technical need to enhance the 1–10 day prediction accuracy of polar motion (PM) in satellite autonomous navigation and deep space exploration, with a focus on optimizing the convolution input accuracy within the least squares and autoregression with effective angular momentum (LS+AR+EAM) method.
Wei Miao, Xueqing Xu, Yonghong Zhou
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