One-step method for predicting LOD parameters based on LS+AR model. Issue 2 (4th May 2021)

• Record Type: Journal Article
• Authors: Wu, Fei; Chang, Guobin; Deng, Kazhong
• Is Part Of: Journal of spatial science. Volume 66:Issue 2(2021)
• Page Start: 317
• Page End: 328
• Publication Date: 2021-05-04
• Subjects: Length of day -- prediction -- least-squares -- autoregressive model -- one step; Geographic information systems -- Periodicals; Cartography -- Periodicals; Surveying -- Periodicals; Geodesy -- Periodicals; Photogrammetry -- Periodicals; Cartography; Geodesy; Geographic information systems; Photogrammetry; Surveying; Periodicals; 526.05
• DOI: 10.1080/14498596.2019.1618401
• Languages: English
• ISSNs: 1449-8596

Abstract

ABSTRACT: This paper proposes a one-step forecasting method based on the LS+AR prediction model that calculates LS and AR model parameters simultaneously. The EOPs products released by the IERS were used as primary data to predict changes in LOD parameters over spans of 1–500 days for 1230 experiments. The experimental results showed that the proposed method has an obvious improvement in long-term LOD parameters prediction accuracy compared with the LS+AR mode. However, limited by the large matrix in the calculation process, the computational efficiency of the proposed method needs to be further improved.