Please use this identifier to cite or link to this item: http://dx.doi.org/10.14279/depositonce-11840
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Main Title: Earth orientation parameters from VLBI determined with a Kalman filter
Author(s): Karbon, Maria
Soja, Benedikt
Nilsson, Tobias
Deng, Zhiguo
Heinkelmann, Robert
Schuh, Harald
Type: Article
Language Code: en
Abstract: This paper introduces the reader to our Kalman filter developed for geodetic VLBI (very long baseline interferometry) data analysis. The focus lies on the EOP (Earth Orientation Parameter) determination based on the Continuous VLBI Campaign 2014 (CONT14) data, but also earlier CONT campaigns are analyzed. For validation and comparison purposes we use EOP determined with the classical LSM (least squares method) estimated from the same VLBI data set as the Kalman solution with a daily resolution. To gain higher resolved EOP from LSM we run solutions which yield hourly estimates for polar motion and dUT1 = Universal Time (UT1) – Coordinated Universal Time (UTC). As an external validation data set we use a GPS (Global Positioning System) solution providing hourly polar motion results. Further, we describe our approach for determining the noise driving the Kalman filter. It has to be chosen carefully, since it can lead to a significant degradation of the results. We illustrate this issue in context with the de-correlation of polar motion and nutation. Finally, we find that the agreement with respect to GPS can be improved by up to 50% using our filter compared to the LSM approach, reaching a similar precision than the GPS solution. Especially the power of erroneous high-frequency signals can be reduced dramatically, opening up new possibilities for high-frequency EOP studies and investigations of the models involved in VLBI data analysis. We prove that the Kalman filter is more than on par with the classical least squares method and that it is a valuable alternative, especially on the advent of the VLBI2010 Global Observing System and within the GGOS frame work.
URI: https://depositonce.tu-berlin.de/handle/11303/13042
http://dx.doi.org/10.14279/depositonce-11840
Issue Date: 6-Sep-2017
Date Available: 16-Apr-2021
DDC Class: 550 Geowissenschaften
Subject(s): VLBI
earth rotation
CONT14
Kalman filter
data analysis
least squares
GPS
License: https://creativecommons.org/licenses/by-nc-nd/4.0/
Journal Title: Geodesy and Geodynamics
Publisher: Elsevier
Publisher Place: Amsterdam
Volume: 8
Issue: 6
Publisher DOI: 10.1016/j.geog.2017.05.006
Page Start: 396
Page End: 407
ISSN: 1674-9847
Appears in Collections:FG Satellitengeodäsie » Publications

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