Centre de documentation
scientifique

Carrier phase bias estimation of geometry-free linear combination of GNSS signals for ionospheric TEC modeling / Anna Krypiak-Gregorczyk in GPS solutions, vol 22 n° 2 (April 2018)  

Public [article]  inGPS solutions > vol 22 n° 2 (April 2018) . - pp 22 - 45 Titre : Carrier phase bias estimation of geometry-free linear combination of GNSS signals for ionospheric TEC modeling Type de document : Article/Communication Auteurs : Anna Krypiak-Gregorczyk, Auteur ; Pawel Wielgosz, Auteur Année de publication : 2018 Article en page(s) : pp 22 - 45 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] combinaison linéaire [Termes IGN] erreur systématique [Termes IGN] modèle ionosphérique [Termes IGN] phase [Termes IGN] positionnement par GNSS [Termes IGN] retard ionosphèrique [Termes IGN] signal GNSS [Termes IGN] teneur totale en électrons [Vedettes matières IGN] Traitement de données GNSS Résumé : (Auteur) The ionosphere can be modeled and studied using multi-frequency GNSS signals and their geometry-free linear combination. Therefore, a number of GNSS-derived ionospheric models have been developed and applied in a broad range of applications. However, due to the complexity of estimating the carrier phase ambiguities, most of these models are based on low-accuracy carrier phase smoothed pseudorange data. This, in turn, critically limits their accuracy and applicability. Therefore, we present a new methodology of estimating the phase bias of the scaled L1 and L2 carrier phase difference which is a function of the ambiguities, the ionospheric delay, and hardware delays. This methodology is suitable for ionospheric modeling at regional and continental scales. In addition, we present its evaluation under varying ionospheric conditions. The test results show that the carrier phase bias of geometry-free linear combination can be estimated with a very high accuracy, which consequently allows for calculating ionospheric TEC with the uncertainty lower than 1.0 TECU. This high accuracy makes the resulting ionosphere model suitable for improving GNSS positioning for high-precision applications in geosciences. Numéro de notice : A2018-160 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s10291-018-0711-4 Date de publication en ligne : 16/02/2018 En ligne : https://doi.org/10.1007/s10291-018-0711-4 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89783 [article]