11 citations as recorded by crossref.

1. Bandwidth correction of Swarm GPS carrier phase observations for improved orbit and gravity field determination L. Schreiter et al. https://doi.org/10.1007/s10291-021-01107-0
2. What can be expected from GNSS tracking of satellite constellations for temporal gravity field model determination? H. Zhou et al. https://doi.org/10.1093/gji/ggaa177
3. Reconstructing GRACE-type time-variable gravity from the Swarm satellites H. Richter et al. https://doi.org/10.1038/s41598-020-80752-w
4. Dynamic GPS-based LEO orbit determination with 1 cm precision using the Bernese GNSS Software X. Mao et al. https://doi.org/10.1016/j.asr.2020.10.012
5. Description of the multi-approach gravity field models from Swarm GPS data J. Teixeira da Encarnação et al. https://doi.org/10.5194/essd-12-1385-2020
6. Bridging the spatiotemporal ice sheet mass change data gap between GRACE and GRACE-FO in Greenland using machine learning method Z. Shi et al. https://doi.org/10.1016/j.jhydrol.2024.130622
7. Improving the Spatial Resolution of GRACE-Derived Ice Sheet Mass Change in Antarctica Z. Shi et al. https://doi.org/10.1109/TGRS.2024.3511944
8. Methodology for the characterisation of the impact of TEC fluctuations and scintillation on ground positioning quality over South America and North Europe, with implications for forecasts B. Forte et al. https://doi.org/10.1016/j.asr.2024.02.033
9. Reprocessed precise science orbits and gravity field recovery for the entire GOCE mission D. Arnold et al. https://doi.org/10.1007/s00190-023-01752-y
10. SLR, GRACE and Swarm Gravity Field Determination and Combination U. Meyer et al. https://doi.org/10.3390/rs11080956
11. Comparison of Data‐Driven Techniques to Reconstruct (1992–2002) and Predict (2017–2018) GRACE‐Like Gridded Total Water Storage Changes Using Climate Inputs F. Li et al. https://doi.org/10.1029/2019WR026551