Centre dedocumentation
scientifique

Long-term prediction of polar motion using a combined SSA and ARMA model / Y. Shen in Journal of geodesy, vol 92 n° 3 (March 2018)  

Public [article]  inJournal of geodesy > vol 92 n° 3 (March 2018) . - pp 333 - 343 Titre : Long-term prediction of polar motion using a combined SSA and ARMA model Type de document : Article/Communication Auteurs : Y. Shen, Auteur ; Jinyun Guo, Auteur ; X. Liu, Auteur ; Qiaoli Kong, Auteur ; Linxi Guo, Auteur ; Li Wang, Auteur Année de publication : 2018 Article en page(s) : pp 333 - 343 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie physique [Termes IGN] analyse de spectre singulier [Termes IGN] analyse en composantes principales [Termes IGN] modèle de simulation [Termes IGN] mouvement du pôle Mots-clés libres : modèle ARMA Résumé : (Auteur) 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 the remaining components were predicted by the ARMA model. In applying this proposed method, multiple sets of PM predictions were made with lead times of two years, based on an IERS 08 C04 series. The observations and predictions of the principal components correlated well, and the SSA + ARMA model effectively predicted the PM. For 360-day lead time predictions, the root-mean-square errors (RMSEs) of PMx and PMy were 20.67 and 20.42 mas, respectively, which were less than the 24.46 and 24.78 mas predicted by IERS Bulletin A. The RMSEs of PMx and PMy in the 720-day lead time predictions were 28.61 and 27.95 mas, respectively. Numéro de notice : A2018-061 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-017-1065-3 Date de publication en ligne : 12/09/2017 En ligne : https://doi.org/10.1007/s00190-017-1065-3 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89397 [article]