Advancements in Ionospheric Modeling: Comparative Analysis of VTEC Derivation from Co-Located VLBI and VGOS Stations
![Thumbnail](/bitstream/handle/20.500.11850/665965/IVS_2024_Rueegg.pdf.jpg?sequence=5&isAllowed=y)
Open access
Date
2024Type
- Other Conference Item
ETH Bibliography
yes
Altmetrics
Abstract
Accurate ionospheric models are essential for precise processing of single-frequency receivers in the microwave regime, such as smartphone receivers for Global Navigation Satellite Systems (GNSS) data. Currently, the predominant models primarily originate from GNSS data, leveraging its continuous and extensive global data coverage. Yet, Very Long Baseline Interferometry (VLBI) offers an alternative approach to determine Vertical Total Electron Content (VTEC), a fundamental metric that offers valuable insights into the ionosphere. Future prospects include the potential utilization of VLBI observations to enhance ionospheric models if the robustness and reliability of the derived values are sufficient. The recent operationalization of the VLBI Global Observing System (VGOS) has further enhanced the potential for VTEC derivation with its four frequency bands. We have developed an iterative least squares algorithm for deriving VTEC values above each station, applicable to both VLBI and VGOS sessions. Our study focuses on the analysis of operational 24-hour sessions, specifically targeting sessions post the CONT17 campaign We concentrate on co-located stations where both VLBI and VGOS sessions occur simultaneously, offering a unique opportunity for comparative analysis. The derived VTEC values from our algorithm are analyzed to assess their consistency and reliability. To further validate our findings, we utilize two independent GNSS-based datasets, namely Global Ionosphere Maps (GIM) and Madrigal TEC Maps (MTM). Initial results reveal a reduced standard deviation of differences and higher correlation between VGOS and GIM products indicating a more consistent inter-technological bias compared to VLBI. Show more
Permanent link
https://doi.org/10.3929/ethz-b-000665965Publication status
publishedExternal links
Publisher
ZenodoEvent
Organisational unit
09707 - Soja, Benedikt / Soja, Benedikt
More
Show all metadata
ETH Bibliography
yes
Altmetrics