Scale and Geocenter determination by GNSS only

A Global Geodetic Reference Frame (GGRF) is a fundamental requirement to relate measurements taken from anywhere on the Earth. It provides the basis on which a broad spectrum of scientific and industrial applications rely, and is crucial in any field where precise location information is necessary, including monitoring climate change, agriculture, and changes in groundwater.
The working group Satellite Geodesy at the Institute of Geodesy (IFG), Graz University of Technology (TUG) provide a wide range of of products which are processed and published to the international community such as gravity field ans mass transport solutions, Precise Orbit Data (POD) of Low Earth Orbit (LEO) satellites and Global Navigation Satellite Systems (GNSS) station networks and much more. The products are utilized by various organizations, such as the International Combination Service for Time-variable Gravity Fields (COST-G) of the International Association of Geodesy (IAG), the International GNSS Service (IGS) or the European Copernicus POD Service Quality Working Group (CPOD). A consistent and accurate GGRF is the foundation of all our products and, as such, is essential to ensure the quality of our in-house computed products.
A GGRF is established and maintained by an international community, culminating in the International Terrestrial Reference Frames (ITRF). The latest version, ITRF2020, is based on four space geodetic techniques: GNSS, VLBI, SLR, and DORIS. In ITRF2020, GNSS was ignored in the calculation of the geocenter motion and the estimation of the reference system scale because it was considered too inaccurate. 
In this work we present our approach to estimate the geocenter motion and to improve the scale estimation using only GNSS. 
We discuss the problems of combined estimation of geocenter motion, reference system scale and satellite antenna center offsets and variations in GNSS only reference frame estimation. We analyze the results and implications for GNSS products and station position time series.