Articles | Volume 38, issue 1
https://doi.org/10.5194/angeo-38-179-2020
https://doi.org/10.5194/angeo-38-179-2020
Regular paper
 | 
06 Feb 2020
Regular paper |  | 06 Feb 2020

Observing geometry effects on a Global Navigation Satellite System (GNSS)-based water vapor tomography solved by least squares and by compressive sensing

Marion Heublein, Patrick Erik Bradley, and Stefan Hinz

Related authors

MATHEMATICAL AND PHYSICAL APPROACHES TO INFER ABSOLUTE ZENITH WET DELAYS FROM DOUBLE DIFFERENTIAL INTERFEROMETRIC OBSERVATIONS USING ERA5 ATMOSPHERIC REANALYSIS
B. Kamm, A. Schenk, P. Yuan, and S. Hinz
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-M-1-2023, 153–159, https://doi.org/10.5194/isprs-archives-XLVIII-M-1-2023-153-2023,https://doi.org/10.5194/isprs-archives-XLVIII-M-1-2023-153-2023, 2023
Tropospheric water vapor: a comprehensive high-resolution data collection for the transnational Upper Rhine Graben region
Benjamin Fersch, Andreas Wagner, Bettina Kamm, Endrit Shehaj, Andreas Schenk, Peng Yuan, Alain Geiger, Gregor Moeller, Bernhard Heck, Stefan Hinz, Hansjörg Kutterer, and Harald Kunstmann
Earth Syst. Sci. Data, 14, 5287–5307, https://doi.org/10.5194/essd-14-5287-2022,https://doi.org/10.5194/essd-14-5287-2022, 2022
Short summary
PREFACE: TECHNICAL COMMISSION I
S. Hinz, R. Q. Feitosa, M. Weinmann, and B. Jutzi
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B1-2022, 7–7, https://doi.org/10.5194/isprs-archives-XLIII-B1-2022-7-2022,https://doi.org/10.5194/isprs-archives-XLIII-B1-2022-7-2022, 2022
COMPARISON AND EVALUATION OF DIFFERENT APPROACHES FOR EFFICIENT PROCESSING OF LONG GROUND-BASED SAR TIMES SERIES
M. Rebmeister, A. Schenk, and S. Hinz
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2022, 341–348, https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-341-2022,https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-341-2022, 2022
PREFACE: TECHNICAL COMMISSION I
S. Hinz, R. Q. Feitosa, M. Weinmann, and B. Jutzi
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-1-2022, 7–7, https://doi.org/10.5194/isprs-annals-V-1-2022-7-2022,https://doi.org/10.5194/isprs-annals-V-1-2022-7-2022, 2022

Related subject area

Subject: Terrestrial atmosphere and its relation to the sun | Keywords: Modelling of the atmosphere
Analysis of migrating and non-migrating tides of the Extended Unified Model in the mesosphere and lower thermosphere
Matthew J. Griffith and Nicholas J. Mitchell
Ann. Geophys., 40, 327–358, https://doi.org/10.5194/angeo-40-327-2022,https://doi.org/10.5194/angeo-40-327-2022, 2022
Short summary
Winds and tides of the Extended Unified Model in the mesosphere and lower thermosphere validated with meteor radar observations
Matthew J. Griffith, Shaun M. Dempsey, David R. Jackson, Tracy Moffat-Griffin, and Nicholas J. Mitchell
Ann. Geophys., 39, 487–514, https://doi.org/10.5194/angeo-39-487-2021,https://doi.org/10.5194/angeo-39-487-2021, 2021
Short summary
Propagation to the upper atmosphere of acoustic-gravity waves from atmospheric fronts in the Moscow region
Yuliya Kurdyaeva, Sergey Kulichkov, Sergey Kshevetskii, Olga Borchevkina, and Elena Golikova
Ann. Geophys., 37, 447–454, https://doi.org/10.5194/angeo-37-447-2019,https://doi.org/10.5194/angeo-37-447-2019, 2019
Short summary
Sensitivity of GNSS tropospheric gradients to processing options
Michal Kačmařík, Jan Douša, Florian Zus, Pavel Václavovic, Kyriakos Balidakis, Galina Dick, and Jens Wickert
Ann. Geophys., 37, 429–446, https://doi.org/10.5194/angeo-37-429-2019,https://doi.org/10.5194/angeo-37-429-2019, 2019
Short summary
Comparisons between the WRF data assimilation and the GNSS tomography technique in retrieving 3-D wet refractivity fields in Hong Kong
Zhaohui Xiong, Bao Zhang, and Yibin Yao
Ann. Geophys., 37, 25–36, https://doi.org/10.5194/angeo-37-25-2019,https://doi.org/10.5194/angeo-37-25-2019, 2019
Short summary

Cited articles

Aguilera, E., Nannini, M., and Reigber, A.: A data-adaptive compressed sensing approach to polarimetric SAR tomography of forested areas, IEEE Geosci. Remote Sens. Lett., 10, 543–547, 2013. a
Alonso, M. T., López-Dekker, P., and Mallorquí, J. J.: A novel strategy for radar imaging based on compressive sensing, IEEE T. Geosci. Remote Sens., 48, 4285–4295, 2010. a
Baraniuk, R.: Compressive sensing, IEEE Signal Proc. Mag., 24, 118–120, 2007. a
Bender, M. and Raabe, A.: Preconditions to ground based GPS water vapour tomography, Ann. Geophys., 25, 1727–1734, https://doi.org/10.5194/angeo-25-1727-2007, 2007. a
Bender, M., Dick, G., Wickert, J., Ramatschi, M., Ge, M., Gendt, G., Rothacher, M., Raabe, A., and Tetzlaff, G.: Estimates of the information provided by GPS slant data observed in Germany regarding tomographic applications, J. Geophys. Res.-Atmos., 114, D06303, https://doi.org/10.1029/2008JD011008, 2009. a