Identifying optimal tag-along station locations for improving VLBI Intensive sessions

Very Long Baseline Interferometry (VLBI) is a unique space-geodetic technique capable of direct observation of the Earth’s phase of rotation, namely Universal Time (UT1). The International VLBI Service for Geodesy and Astrometry (IVS) conducts daily 1-h Intensive VLBI sessions to determine rapid variations in the difference between UT1 and Coordinated Universal Time (UTC). The main objective of the Intensive sessions is to provide timely UT1–UTC estimates. These estimates are especially crucial for Global Navigation Satellite Systems (GNSS). The monitoring of rapid variations in Earth rotation also provides insight into various geophysical phenomena. There is an ongoing effort to improve the quality of the UT1–UTC estimates from single-baseline Intensive sessions to realise the expected accuracy and to bring them to a better agreement with the 24-h VLBI sessions. In this paper, we investigate the possibility to improve the Intensives by including a third station in tag-along mode to these regularly observed sessions. The impact of the additional station is studied via extensive simulations using the c5++ analysis software. The location of the station is varied within a predetermined grid. Based on actual Intensive session schedules, a set of simulated observations are generated for the two original stations and each grid point. These simulated data are used to estimate UT1–UTC for every Intensive session scheduled during the year 2014 on the Kokee–Wettzell and Tsukuba–Wettzell baselines, with the addition of a third station. We find that in tag-along mode when a third station is added to the schedule we can identify areas where the UT1–UTC estimates are improved up to 67% w.r.t. the original single-baseline network. There are multiple operational VLBI stations in these areas, which could with little effort be included in a tag-along mode to the currently scheduled Intensive sessions, thus providing the possibility to improve the UT1–UTC estimates by extending the observation network