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Medientyp:
E-Artikel;
Sonstige Veröffentlichung
Titel:
Estimation and Validation of Codephase Center Correction Using the Empirical Mode Decomposition
Beteiligte:
Breva, Yannick
[Verfasser:in];
Kröger, Johannes
[Verfasser:in];
Kersten, Tobias
[Verfasser:in];
Schön, Steffen
[Verfasser:in];
Freymueller, Jeffrey T.
[Verfasser:in];
Sánchez, Laura
[Verfasser:in]
Erschienen:
Berlin; Heidelberg : Springer, 2022
Erschienen in:Geodesy for a Sustainable Earth : Proceedings of the 2021 Scientific Assembly of the International Association of Geodesy ; International Association of Geodesy symposia : IAG ; 154
Anmerkungen:
Diese Datenquelle enthält auch Bestandsnachweise, die nicht zu einem Volltext führen.
Beschreibung:
In high precision Global Navigation Satellite Systems (GNSS) applications, it is necessary to take phase center corrections (PCC) into account. Beside these corrections for carrier phase measurements, also corrections for the codephase are necessary, so called codephase center corrections (CPC). The CPC, also known as group delay variations, are antenna dependent delays of the received codephase, which are varying with azimuth and elevation of the incoming GNSS signal. A concept for estimating absolute CPC and PCC for multi GNSS signals has been established by the Institut für Erdmessung. In this paper, the standard calibration approach with a sampling rate of 1 Hz is briefly described, which works well for PCC estimation. The main challenge of this approach for estimating repeatable CPC patterns is the significantly higher noise to pattern ratio in the observations compared to PCC determination. Therefore, an alternative processing strategy is presented in this contribution. By increasing the sampling rate to 10 Hz, the empirical mode decomposition can be used to reduce the noise of the input observations by maintaining all pattern information. With this method, the calibration repeatability is improved by 46% to 60% for GPS and Galileo C1C signals for a geodetic antenna. Moreover, the estimated pattern is validated in the positioning domain with a single point positioning approach. By considering the estimated CPC the accuracy of the height component can be improved.