Impact of the Source Selection and Scheduling Optimization on the Estimation of UT1-UTC in VLBI Intensive Sessions
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Date
2023-01
Publication Type
Conference Paper
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yes
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Abstract
With the help of Very Long Baseline Interferometry (VLBI), it is possible to determine a large number of parameters, including station and source coordinates as well as the Earth orientation parameters (EOP). Due to the limitation of observations of one hour single baseline sessions, so-called Intensive sessions, only a few parameters such as clock offsets and zenith wet delays per station can be estimated in addi tion to the parameter of primary interest, which is the difference between UT1 (Universal Time 1) and UTC (Coordinated Universal Time). Thus, the remaining parameters, including station and source coordinates, as well as EOP, are fixed to their a priori values, making the precision of the UT1- UTC estimate dependent on the accuracy of the a priori values used in the estimation process. Additionally, due to the daily rotation of the Earth and the revolution around the Sun, the source visibility and selection changes continuously, resulting in variations of the estimates of interest over time. Furthermore, the scheduling optimization process itself also has an impact on the results obtained by real observations or simulations. In this study, we show the variations of UT1-UTC estimates due to varying source selection and scheduling optimization strategies throughout the investigation period of one year using the simulation results of [7].
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Publication status
published
External links
Book title
IVS 2022 General Meeting Proceedings
Journal / series
Volume
Pages / Article No.
167 - 171
Publisher
International VLBI Service for Geodesy and Astrometry (IVS)
Event
12th IVS General Meeting (GM 2022)
Edition / version
Methods
Software
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Date collected
Date created
Subject
VLBI; Intensives; Simulation; UTI-UTC
Organisational unit
09707 - Soja, Benedikt / Soja, Benedikt
Notes
Conference lecture held on March 31, 2022.
Funding
Related publications and datasets
Is part of: https://ivscc.gsfc.nasa.gov/publications/gm2022/