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Impact of the Source Selection and Scheduling Optimization on the Estimation of UT1-UTC in VLBI Intensive Sessions [PDF]

open access: yes, 2023
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 ...
Kern, Lisa Maria   +5 more
openaire   +2 more sources
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Middle and long-term prediction of UT1-UTC based on combination of Gray Model and Autoregressive Integrated Moving Average

Advances in Space Research, 2017
Abstract UT1-UTC is an important part of the Earth Orientation Parameters (EOP). The high-precision predictions of UT1-UTC play a key role in practical applications of deep space exploration, spacecraft tracking and satellite navigation and positioning.
Song Jia   +3 more
exaly   +2 more sources

Prediction of UT1-UTC Based on Combination of Weighted Least-Squares and Multivariate Autoregressive

Lecture Notes in Electrical Engineering, 2013
High accurate prediction of UT1-UTC is very important for high-precision aircraft navigation and positioning. In this paper, the weighted least-squares (WLS) combined with multivariate autoregressive (MAR) is proposed to predict UT1-UTC with different span.
Zhang-zhen Sun, Tian-he Xu
exaly   +2 more sources

Prediction of UT1-UTC by machine learning techniques

2022
<p>Machine Learning (ML) algorithms are used to learn from data and make data-driven predictions. These algorithms consider pattern recognition and computational learning on the data. Earth Orientation Parameters (EOP) are the monitoring parameters for the Earth’s rotation.
Sujata Dhar   +5 more
openaire   +2 more sources

Prediction Analysis of UT1-UTC Time Series by Combination of the Least-Squares and Multivariate Autoregressive Method [PDF]

open access: possible, 2011
The objective of this paper is to extensively discuss the theory behind the multivariate autoregressive prediction technique used elsewhere for forecasting Universal Time (UT1-UTC) and to characterise its performance depending on input geodetic and geophysical data.
Tomasz Niedzielski, Wiesław Kosek
openaire   +1 more source

Revisiting European VLBI Intensives for Rapid UT1-UTC Determination

Accurate, low-latency UT1–UTC estimates are essential for monitoring Earth’s highly variable rotation and for real-time applications ranging from GNSS to lunar and deep-space missions. One-hour VLBI Intensive sessions, typically conducted with two stations on long east–west baselines, have the primary goal of providing rapid UT1–UTC estimates.
Lisa Kern   +5 more
openaire   +1 more source

Investigating the impact of IERS and IVS data as input for ultra-short-term prediction of UT1-UTC

The Earth’s rotation phase, expressed as UT1-UTC, is the most crucial geodetic parameter that can only be precisely measured using Very Long Baseline Interferometry (VLBI), although with considerable latency. Reliable predictions of UT1-UTC are essential for real-time positioning and navigation, and thus several approaches have been developed to ...
Arnab LAHA   +4 more
openaire   +1 more source

Dynamic Mode Decomposition-based short-term prediction of UT1-UTC and LOD using Atmospheric Angular Momentum time series.

We present preliminary results of ultra-short-term prediction (10-day forecast horizon) of UT1-UTC and LOD. Forecast procedure is based on Dynamic Mode Decomposition (DMD) and uses IERS EOP 14 C04 as a reference as well as Atmospheric Angular Momentum (AAM) as auxiliary data (AAM come from GFZ Potsdam and ETH Zurich).Two main prediction experiments ...
Maciej Michalczak   +3 more
openaire   +1 more source

Wavelet Analysis of high-frequency UT1-UTC varia¬tions

1999
Titov, O.   +1 more
openaire   +1 more source

The UT1 and UTC Time Services Provided by the National Institute of Standards and Technology

Thirty Years of Astronomical Discovery With UKIRT, 2017
Judah Levine
exaly  

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