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arXiv · 2311.18621

Evaluating the feasibility of short-integration scans based on the 2022 VGOS-R&D program

Abstract

In this work, we report on activities focusing on improving the observation strategy of the Very Long Baseline Interferometry (VLBI) Global Observing System (VGOS). During six dedicated 24-hour Research and Development (R&D) sessions conducted in 2022, the effectiveness of a signal-to-noise ratio (SNR)-based scheduling approach with observation times as short as 5-20 seconds was explored. The sessions utilized a full 8 Gbps observing mode and incorporated elements such as dedicated calibration scans, a VGOS frequency source-flux catalog, improved sky-coverage parameterization, and more. The number of scans scheduled per station increased by 2.34 times compared to operational VGOS-OPS sessions, resulting in a 2.58 times increase in the number of observations per station. Remarkably, the percentage of successful observations per baseline matched the fixed 30-second observation approach employed in VGOS-OPS, demonstrating the effectiveness of the SNR-based scheduling approach. The impact on the geodetic results was examined based on statistical analysis, revealing a significant improvement when comparing the VGOS-R\&D program with VGOS-OPS. The formal errors in estimated station coordinates decreased by 50 %. The repeatability of baseline lengths improved by 30 %, demonstrating the enhanced precision of geodetic measurements. Furthermore, Earth orientation parameters exhibited substantial improvements, with a 60 % reduction in formal errors, 27 % better agreement w.r.t. IVS-R1/R4, and 13 % better agreement w.r.t. IERS EOP 20C04. Overall, these findings strongly indicate the superiority of the VGOS-R&D program, positioning it as a role model for future operational VGOS observations.

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BibTeXRIS

Matthias Schartner, Bill Petrachenko, Mike Titus, Hana Krasna, John Barrett, Dan Hoak, Dhiman Mondal, Minghui Xu, Benedikt Soja. 2023-11-30. Evaluating the feasibility of short-integration scans based on the 2022 VGOS-R&D program. https://arxiv.org/abs/2311.18621

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