EGU21-3177
https://doi.org/10.5194/egusphere-egu21-3177
EGU General Assembly 2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

Analysis of differential residuals of SLR observations to GNSS: Methodology and results from analyzing 25 years of data

Dimitrios Ampatzidis, Daniela Thaller, and Lin Wang
Dimitrios Ampatzidis et al.
  • Federal Agency for Cartography and Geodesy (BKG), G1, Frankfurt a.M., Germany (dimitrios.ampatzidis@bkg.bund.de)

The SLR observations to GNSS play a significant role as space tie, and allow investigations of many quantities related to the global Terrestrial Reference Frames (TRF), e.g., satellite orbits, scale, station coordinates, local ties. The differences between the observed ranges (via SLR observations) minus the computed spatial distances (via GNSS orbits based on GNSS observations) form the so-called “SLR residuals”. The analysis of these SLR residuals offers the opportunity to investigate the biases of the SLR measurements, the quality of the GNSS orbits and the quality and consistency of station coordinates. However, the absolute residuals contain a various number of inconsistencies and systematics which are not straightforward to be identified and separated, and, therefore to be further investigated. The present study focuses on the derivation of three alternative scenarios/cases through the usage of differential residuals between epochs, satellites and stations. These differential SLR residuals are derived from the processing of 25 years of SLR observations to GNSS (using GPS and GLONASS). The advantage of using the differential residuals is the elimination of one or more sources of systematic errors, according to each scenario. The comparison between the absolute and the differential residuals, respectively, is proven to stand as a useful diagnostic tool for the assessment of the systematic effects.

How to cite: Ampatzidis, D., Thaller, D., and Wang, L.: Analysis of differential residuals of SLR observations to GNSS: Methodology and results from analyzing 25 years of data, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-3177, https://doi.org/10.5194/egusphere-egu21-3177, 2021.

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