Artificial satellites / Space research centre of polish academy of sciences . vol 51 n° 4Paru le : 01/12/2016 |
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Ajouter le résultat dans votre panierComplex demodulation in monitoring earth rotation by VLBI: testing the algorithm by analysis of long periodic EOP components / Agata Wielgosz in Artificial satellites, vol 51 n° 4 (December 2016)
[article]
Titre : Complex demodulation in monitoring earth rotation by VLBI: testing the algorithm by analysis of long periodic EOP components Type de document : Article/Communication Auteurs : Agata Wielgosz, Auteur Année de publication : 2016 Article en page(s) : pp 135 – 147 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale
[Termes IGN] interférométrie à très grande base
[Termes IGN] modulation du signal
[Termes IGN] orientation de la Terre
[Termes IGN] rotation de la Terre
[Termes IGN] série temporelleRésumé : (auteur) The complex demodulation (CD) algorithm is an efficient tool for extracting the diurnal and subdiurnal components of Earth rotation from the routine VLBI observations (Brzeziński, 2012). This algorithm was implemented by Böhm et al (2012b) into a dedicated version of the VLBI analysis software VieVs. The authors processed around 3700 geodetic 24-hour observing sessions in 1984.0-2010.5 and estimated simultaneously the time series of the long period components as well as diurnal, semidiurnal, terdiurnal and quarterdiurnal components of polar motion (PM) and universal time UT1. This paper describes the tests of the CD algorithm by checking consistency of the low frequency components of PM and UT1 estimated by VieVS CD and those from the IERS and IVS combined solutions. Moreover, the retrograde diurnal component of PM demodulated from VLBI observations has been compared to the celestial pole offsets series included in the IERS and IVS solutions. We found for all three components a good agreement of the results based on the CD approach and those based on the standard parameterization recommended by the IERS Conventions (IERS, 2010) and applied by the IERS and IVS. We conclude that an application of the CD parameterization in VLBI data analysis does not change those components of EOP which are included in the standard adjustment, while enabling simultaneous estimation of the high frequency components from the routine VLBI observations. Moreover, we deem that the CD algorithm can also be implemented in analysis of other space geodetic observations, like GNSS or SLR, enabling retrieval of subdiurnal signals in EOP from the past data. Numéro de notice : A2016-976 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : 10.1515/arsa-2016-0012 En ligne : https://doi.org/10.1515/arsa-2016-0012 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83687
in Artificial satellites > vol 51 n° 4 (December 2016) . - pp 135 – 147[article]Ultra short-term prediction of pole coordinates via combination of empirical mode decomposition and neural networks / Yu Lei in Artificial satellites, vol 51 n° 4 (December 2016)
[article]
Titre : Ultra short-term prediction of pole coordinates via combination of empirical mode decomposition and neural networks Type de document : Article/Communication Auteurs : Yu Lei, Auteur ; Danning Zhao, Auteur ; Hongbing Cai, Auteur Année de publication : 2016 Article en page(s) : pp 149 – 161 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie physique
[Termes IGN] filtre passe-bas
[Termes IGN] fonction de base radiale
[Termes IGN] mouvement du pôle
[Termes IGN] oscillation
[Termes IGN] prévision à court terme
[Termes IGN] réseau neuronal artificiel
[Termes IGN] terme de ChandlerRésumé : (auteur) It was shown in the previous study that the increase of pole coordinates prediction error for about 100 days in the future is mostly caused by irregular short period oscillations. In this paper, the ultra short-term prediction of pole coordinates is studied for 10 days in the future by means of combination of empirical mode decomposition (EMD) and neural networks (NN), denoted EMD-NN. In the algorithm, EMD is employed as a low pass filter for eliminating high frequency signals from observed pole coordinates data. Then the annual and Chandler wobbles are removed a priori from pole coordinates data with high frequency signals eliminated. Finally, the radial basis function (RBF) networks are used to model and predict the residuals. The prediction performance of the EMD-NN approach is compared with that of the NN-only solution and the prediction methods and techniques involved in the Earth orientation parameters prediction comparison campaign (EOP PCC). The results show that the prediction accuracy of the EMD-NN algorithm is better than that of the NN-only solution and is also comparable with that of the other existing prediction method and techniques. Numéro de notice : A2016-977 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : 10.1515/arsa-2016-0013 En ligne : https://doi.org/10.1515/arsa-2016-0013 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83688
in Artificial satellites > vol 51 n° 4 (December 2016) . - pp 149 – 161[article]