Skip to main content

Main menu

  • Home
  • Current Issue
  • Archive
  • About Us
    • About NAVIGATION
    • Editorial Board
    • Peer Review Statement
    • Open Access
  • More
    • Email Alerts
    • Info for Authors
    • Info for Subscribers
  • Other Publications
    • ion

User menu

  • My alerts

Search

  • Advanced search
NAVIGATION: Journal of the Institute of Navigation
  • Other Publications
    • ion
  • My alerts
NAVIGATION: Journal of the Institute of Navigation

Advanced Search

  • Home
  • Current Issue
  • Archive
  • About Us
    • About NAVIGATION
    • Editorial Board
    • Peer Review Statement
    • Open Access
  • More
    • Email Alerts
    • Info for Authors
    • Info for Subscribers
  • Follow ion on Twitter
  • Visit ion on Facebook
  • Follow ion on Instagram
  • Visit ion on YouTube
Research ArticleOriginal Article
Open Access

A collocation framework to retrieve tropospheric delays from a combination of GNSS and InSAR

Endrit Shehaj, Karina Wilgan, Othmar Frey and Alain Geiger
NAVIGATION: Journal of the Institute of Navigation December 2020, 67 (4) 823-842; DOI: https://doi.org/10.1002/navi.398
Endrit Shehaj
1Institute of Geodesy and Photogrammetry, ETH Zürich, Zürich, Switzerland
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • For correspondence: [email protected]
Karina Wilgan
1Institute of Geodesy and Photogrammetry, ETH Zürich, Zürich, Switzerland
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Othmar Frey
2Institute of Environmental Engineering, ETH Zürich, Zürich, Switzerland
3Gamma Remote Sensing, Gümligen, Switzerland
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Alain Geiger
1Institute of Geodesy and Photogrammetry, ETH Zürich, Zürich, Switzerland
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • Article
  • Figures & Data
  • Supplemental
  • References
  • Info & Metrics
  • PDF
Loading

REFERENCES

  1. ↵
    1. Alshawaf, F.
    (2013). Constructing water vapor maps by fusing InSAR, GNSS and WRF data (Doctoral dissertation, Karlsruhe Institute of Technology). https://publikationen.bibliothek.kit.edu/1000038846
  2. ↵
    1. Askne, J., &
    2. Nordius, H.
    (1987). Estimation of tropospheric delay for microwaves from surface weather data. Radio Science, 22(3), 379–386. https://doi.org/10.1029/RS022i003p00379
    CrossRefWeb of Science
  3. ↵
    1. Bekaert, D.,
    2. Hooper, A., &
    3. Wright, T.
    (2015). A spatially variable power lawtropospheric correction technique for InSAR data. Journal of Geophysical Research: Solid Earth, 120, 1345–1356. https://doi.org/10.1002/2014JB011558
    1. Bekaert, D.,
    2. Walters, R.,
    3. Wright, T.,
    4. Hooper, A., &
    5. Parker, D.
    (2015). Statistical comparison of InSAR tropospheric correction techniques. Remote Sensing of Environment, 170, 40–47. https://doi.org/10.1016/j.rse.2015.08.035
  4. ↵
    1. Bevis, M.,
    2. Businger, S.,
    3. Herring, T. A.,
    4. Rocken, C.,
    5. Anthes, R. A., &
    6. Ware, R. H.
    (1992). GPS meteorology: Remote sensing of atmospheric water vapor using the Global Positioning System. Journal of Geophysical Research, 97, 15787–15801. https://doi.org/10.1029/92JD01517
    CrossRefWeb of Science
  5. ↵
    1. Black, H. D., &
    2. Eisner, A.
    (1984). Correcting satellite Doppler data for tropospheric effects. Journal of Geophysical Research, 89, 2616–2626. https://doi.org/10.1029/JD089iD02p02616
  6. ↵
    1. Boehm, J.,
    2. Niell, A.,
    3. Tregoning, P., &
    4. Schuh, H.
    (2006). Global Mapping Function (GMF): A new empirical mapping function based on numerical weather model data. Geophysical Research Letters, 33, L07304. https://doi.org/10.1029/2005GL025546
    CrossRef
  7. ↵
    1. Cavalié, O.,
    2. Doin, M. P.,
    3. Lasserre, C., &
    4. Briole, P.
    (2007). Ground motion measurement in the Lake Mead area, Nevada, by differential synthetic aperture radar interferometry time series analysis: Probing the lithosphere rheological structure. Journal of Geophysical Research, 112, B03403. https://doi.org/10.1029/2006JB004344
  8. ↵
    1. Champollion, C.,
    2. Masson, F.,
    3. Bouin, M. N.,
    4. Walpersdorf, A.,
    5. Doerflinger, E.,
    6. Bock, O., &
    7. van Baelen, J.
    (2005). GPS water vapour tomography: Preliminary results from the ESCOMPTE field experiment. Atmospheric Research, 74(1), 253–274. https://doi.org/10.1016/j.atmosres.2004.04.003
  9. ↵
    1. Collins, J. P.
    (1999). Assessment and development of a tropospheric delay model for aircraft users of the Global Positioning System (Master’s thesis). Available from Department of Geodesy and Geomatics Engineering, University of New Brunswick. (Technical Report No. 203).
  10. ↵
    1. Dach, R.,
    2. Lutz, S.,
    3. Walser, P., &
    4. Fridez, P.
    (2015). Bernese GNSS software version 5.2. Astronomical Institute, University of Bern.
  11. ↵
    1. Davis, J. L.,
    2. Cosmo, M. L., &
    3. Elgered, G.
    (1996). Using the Global Positioning System to study the atmosphere of the Earth: Overview and prospects. In G. Beutler, W. G. Melbourne, G. W. Hein, & G. Seeber (Eds.), GPS trends in precise terrestrial, airborne, and spaceborne applications (pp. 233–242). Springer.
  12. ↵
    1. Eckert, V.,
    2. Cocard, M., &
    3. Geiger, A.
    (1992a). COMEDIE: (Collocation of meteorological data for interpretation and estimation of tropospheric pathdelays) Teil I: Konzepte, Teil II: Resultate (Technical Report 194). ETH Zürich, Grauer Bericht.
  13. ↵
    1. Eckert, V.,
    2. Cocard, M., &
    3. Geiger, A.
    (1992b). COMEDIE: (Collocation of meteorological data for interpretation and estimation of tropospheric pathdelays) Teil III: Software (Technical Report 195). ETH Zürich, Grauer Bericht.
  14. ↵
    1. Elgered, G.,
    2. Johansson, J. M.,
    3. Rönnäng, B. O., &
    4. Davis, J. L.
    (1997). Measuring regional atmospheric water vapor using the Swedish permanent GPS network. Geophysical Research Letters, 24(21), 2663–2666. https://doi.org/10.1029/97GL02798
  15. ↵
    1. Essen, L., &
    2. Froome, K. D.
    (1951). The refractive indices and dielectric constants of air and its principal constituents at 24,000 Mc/s. Proceedings of the Physical Society, 64(10), 2862. https://doi.org/10.1088/0370-1301/64/10/303
  16. ↵
    1. Ferretti, A.,
    2. Prati, C., &
    3. Rocca, F.
    (2001). Permanent scatterers in SAR interferometry. IEEE Transactions on Geoscience and Remote Sensing, 39(1), 8–20. https://doi.org/10.1109/36.898661
    CrossRefWeb of Science
  17. ↵
    1. Fornaro, G.,
    2. D’Agostino, N.,
    3. Giuliani, R.,
    4. Noviello, C.,
    5. Reale, D., &
    6. Verde, S.
    (2015). Assimilation of GPS-derived atmospheric propagation delay in DInSAR data processing. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 8, 784–799. https://doi.org/10.1109/JSTARS.2014.2364683
  18. ↵
    1. Geiger, A.
    (1987). Einfluss richtungsabhängiger Fehler bei Satellitenmessungen (Technical Report 130). IGP-ETH Zürich, Grauer Bericht, Zürich.
  19. ↵
    1. Guo, J., &
    2. Langley, R. B.
    (2003, September). A new tropospheric propagation delay mapping function for elevation angles down to 2. Proceedings of the 16th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GPS/GNSS 2003), Portland, OR, 368–376.
  20. ↵
    1. Hanssen, R.
    (2001). Radar interferometry: Data interpolation and error analysis (Vol. 2). Springer Science and Business Media.
  21. ↵
    1. Hanssen, R.,
    2. Weckwerth, T.,
    3. Zebker, H., &
    4. Klees, R.
    (1999). High-resolution water vapor mapping from interferometric radar measurements. Science, 283, 1297–1299. https://doi.org/10.1126/science.283.5406.1297
    Abstract/FREE Full Text
  22. ↵
    1. Heublein, M.
    (2019). GNSS and InSAR based water vapor tomography: A compressive sensing solution (Doctoral dissertation, Karlsruhe Institute of Technology). https://publikationen.bibliothek.kit.edu/1000093403
  23. ↵
    1. Hirter, H.
    (1998). Mehrdimensionale Interpolation von Meteorologischen Feldern zur Berechnung der Brechungsbedingungen in der Geodäsie (Mitteilung 64). Inst. of Geodesy and Photogrammetry, ETH Zurich.
  24. ↵
    1. Hobiger, T.,
    2. Kinoshita, Y.,
    3. Shimizu, S.,
    4. Ichikawa, R.,
    5. Furuya, M.,
    6. Kondo, T., &
    7. Koyama, Y.
    (2010). On the importance of accurately ray-traced troposphere corrections for Interferometric SAR data. Journal of Geodesy, 84(9), 537–546. https://doi.org/10.1007/s00190-010-0393-3
  25. ↵
    1. Hooper, A. J.,
    2. Segall, P., &
    3. Zebker, H.
    (2007). Persistent scatterer InSAR for crustal deformation analysis, with application to Volcán Alcedo, Galápagos. Journal of Geophysical Research, 112, B07407. https://doi.org/10.1029/2006JB004763
    CrossRef
  26. ↵
    1. Hopfield, H. S.
    (1971). Tropospheric effect on electromagnetically measured range: Prediction from surface weather data. Radio Science, 6(3), 357–367. https://doi.org/10.1029/RS006i003p00357
  27. ↵
    1. Hurter, F.
    (2014). GNSS meteorology in spatially dense networks. Geodätisch-geophysikalische Arbeiten in der Schweiz, Swiss Geodetic Commission.
  28. ↵
    1. Kampes, B. M.
    (2005). Displacement parameter estimation using permanent scatterer interferometry (Doctoral dissertation, TU Delft). https://repository.tudelft.nl/islandora/object/uuid%3A9f11f2ef-2db4-4583-a763-aee88e06ee3b
  29. ↵
    1. Kinoshita, Y.,
    2. Furuya, M.,
    3. Hobiger, T., &
    4. Ichikawa, R.
    (2013). Are numerical weather model outputs helpful to reduce tropospheric delay signals in InSAR data? Journal of Geodesy, 87(3), 267–277. https://doi.org/10.1007/s00190-012-0596-x
  30. ↵
    1. Kruse, L. P.
    (2004). Spatial and temporal distribution of atmospheric water vapor using space geodetic techniques. Geodätisch-geophysikalische Arbeiten in der Schweiz, Swiss Geodetic Commission.
  31. ↵
    1. Leandro, R.,
    2. Santos, M., &
    3. Langley, R. B.
    (2006, January). UNB neutral atmosphere models: Development and performance. Proceedings of the 2006 National Technical Meeting of The Institute of Navigation, Monterey, CA, 564–573.
  32. ↵
    1. Leandro, R.,
    2. Santos, M., &
    3. Langley, R. B.
    (2009). A North America wide area neutral atmosphere model for GNSS applications. NAVIGATION, 56(1), 57–71. https://doi.org/10.1002/j.2161-4296.2009.tb00444.x
  33. ↵
    1. Li, Z.,
    2. Fielding, E. J.,
    3. Cross, P., &
    4. Muller, J.
    (2006). Interferometric synthetic aperture radar atmospheric correction: GPS topography-dependent turbulence model. Journal of Geophysical Research, 111, B02404. https://doi.org/10.1029/2005JB003711
  34. ↵
    1. Li, Z.,
    2. Fielding, E.,
    3. Cross, P., &
    4. Preusker, R.
    (2009). Advanced InSAR atmospheric correction: MERIS/MODIS combination and stacked water vapour models. International Journal of Remote Sensing, 30(13), 3343–3363. https://doi.org/10.1080/01431160802562172
  35. ↵
    1. Mateus, P.,
    2. Nico, G.,
    3. Tomé, R.,
    4. Catalao, J., &
    5. Miranda, P. M.
    (2013). Experimental study on the atmospheric delay based on GPS, SAR interferometry, and numerical weather model data. IEEE Transactions on Geoscience and Remote Sensing, 51(1), 6–11. https://doi.org/10.1109/TGRS.2012.2200901
  36. ↵
    MeteoSwiss (2019). COSMO forecasting system. https://www.meteoswiss.admin.ch/home/measurement-and-forecasting-systems/warning-and-forecasting-systems/cosmo-forecasting-system.html
  37. ↵
    1. Möller, G.
    (2017). Reconstruction of 3D wet refractivity fields in the lower atmosphere along bended GNSS signal paths (Doctoral dissertation). Südwestdeutscher Verlag für Hochschulschriften.
  38. ↵
    1. Möller, G.,
    2. Weber, R., &
    3. Böhm, J.
    (2014). Improved troposphere blind models based on numerical weather data. NAVIGATION, 61(3), 203–211. https://doi.org/10.1002/navi.66
  39. ↵
    1. Niell, A. E.
    (1996). Global mapping functions for the atmosphere delay at radio wavelengths. Journal of Geophysical Research, 101(b2), 3227–3246. https://doi.org/10.1029/95JB03048
    CrossRef
  40. ↵
    1. Onn, F.
    (2006). Modeling water vapour using GPS with application to mitigating insar atmospheric distortions (Doctoral dissertation, Stanford University). https://web.stanford.edu/group/radar/people/fayazthesis_lowres.pdf
  41. ↵
    1. Perler, D.
    (2012). Water vapor tomography using Global Navigation Satellite Systems. Geodätisch-geophysikalische Arbeiten in der Schweiz, Swiss Geodetic Commission.
  42. ↵
    1. Puysségur, B.,
    2. Michel, R., &
    3. Avouac, J. P.
    (2007). Tropospheric phase delay in interferometric synthetic aperture radar estimated from meteorological model and multispectral imagery. Journal of Geophysical Research: Solid Earth, 112, B05419. https://doi.org/10.1029/2006JB004352
  43. ↵
    1. Rueger, J. M.
    (2002, April). Refractive index formulae for radio waves, Proceedings of the FIG XXII International Congress, Washington, DC.
  44. ↵
    1. Saastamoinen, J.
    (1973). Contributions to the theory of atmospheric refraction: Part II. Refraction corrections in satellite geodesy. Journal of Geodesy, 107, 13–34. https://doi.org/10.1007/BF02522083
  45. ↵
    1. Siddique, M. A.,
    2. Strozzi, T.,
    3. Hajnsek, I., &
    4. Frey, O.
    (2019). A case study on the correction of atmospheric phases for SAR tomography in mountainous regions. IEEE Transactions on Geoscience and Remote Sensing, 57(1), 416–431. https://doi.org/10.1109/TGRS.2018.2855101
  46. ↵
    Swisstopo (2019). AGNES status/time series. http://pnac.swisstopo.admin.ch/pages/en/agnes-status.html#
  47. ↵
    1. Troller, M.
    (2004). GPS based determination of the integrated and spatially distributed water vapor in the troposphere. Geodätisch-geophysikalische Arbeiten in der Schweiz, Swiss Geodetic Commission.
  48. ↵
    1. Walpersdorf, A.,
    2. Calais, E.,
    3. Haase, J.,
    4. Eymard, L.,
    5. Desbois, M., &
    6. Vedel, H.
    (2001). Atmospheric gradients estimated by GPS compared to a high resolution numerical weather prediction (NWP) model. Physics and Chemistry of the Earth, Part A: Solid Earth and Geodesy, 26, 147–152. https://doi.org/10.1016/S1464-1895(01)00038-2
  49. ↵
    1. Wegmuller, U.,
    2. Walter, D.,
    3. Spreckels, V., &
    4. Werner, C. L.
    (2010). Nonuniform ground motion monitoring with TerraSAR-X Persistent Scatterer Interferometry. IEEE Transactions on Geoscience and Remote Sensing, 48(2), 895–904. https://doi.org/10.1109/TGRS.2009.2030792
    GeoRef
  50. ↵
    1. Wegmuller, U.,
    2. Werner, C. L.,
    3. Strozzi, T., &
    4. Wiesmann, A.
    (2004). Multi-temporal interferometric point target analysis. In P. Smits & L. Bruzzone (Eds.), Analysis of multi-temporal remote sensing images (Vol. 3, pp. 136–144). World Scientific.
  51. ↵
    1. Werner, C. L.,
    2. Wegmuller, U.,
    3. Strozzi, T., &
    4. Wiesmann, A.
    (2003, July). Interferometric point target analysis for deformation mapping. Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, Toulouse, France, 4362–4364 https://doi.org/10.1109/IGARSS.2003.1295516
  52. ↵
    1. Wicks, C. W.,
    2. Dzurisin, D.,
    3. Ingebritsen, S.,
    4. Thatcher, W.,
    5. Lu, Z., &
    6. Iverson, J.
    (2002). Magmatic activity beneath the quiescent Three Sisters volcanic center, central Oregon Cascade Range, USA. Geophysical Research Letters, 29(7), 26-1–26-4. https://doi.org/10.1029/2001GL014205
    CrossRef
  53. ↵
    1. Wilgan, K.,
    2. Hurter, F.,
    3. Geiger, A.,
    4. Rohm, W., &
    5. Bosy, J.
    (2017). Tropospheric refractivity and zenith path delays from least-squares collocation of meteorological and GNSS data. Journal of Geodetic, 91, 117–134. https://doi.org/10.1007/s00190-016-0942-5
  54. ↵
    1. Wilgan, K.,
    2. Siddique, M. A.,
    3. Strozzi, T.,
    4. Geiger, A., &
    5. Frey, O.
    (2019). Comparison of tropospheric path delay estimates from GNSS and space-borne SAR Interferometry in alpine conditions. Remote Sensing, 11(15). https://doi.org/10.3390/rs11151789
  55. ↵
    1. Yuan, L. L.,
    2. Anthes, R. A.,
    3. Ware, R. H.,
    4. Rocken, C.,
    5. Bonner, W. D.,
    6. Bevis, M. G., &
    7. Businger, S.
    (1993). Sensing climate change using the Global Positioning System. Journal of Geophysical Research, 98(D8), 14925–14937. https://doi.org/10.1029/93JD00948
  56. ↵
    1. Zebker, H.,
    2. Rosen, P., &
    3. Hensley, S.
    (1997). Atmospheric effects in interferometric synthetic aperture radar surface deformation and topographic maps. Journal of Geophysical Research: Solid Earth, 102, 7547–7563. https://doi.org/10.1029/96JB03804
PreviousNext
Back to top

In this issue

NAVIGATION: Journal of the Institute of Navigation: 67 (4)
NAVIGATION: Journal of the Institute of Navigation
Vol. 67, Issue 4
Winter 2020
  • Table of Contents
  • Index by author
Print
Download PDF
Article Alerts
Sign In to Email Alerts with your Email Address
Email Article

Thank you for your interest in spreading the word on NAVIGATION: Journal of the Institute of Navigation.

NOTE: We only request your email address so that the person you are recommending the page to knows that you wanted them to see it, and that it is not junk mail. We do not capture any email address.

Enter multiple addresses on separate lines or separate them with commas.
A collocation framework to retrieve tropospheric delays from a combination of GNSS and InSAR
(Your Name) has sent you a message from NAVIGATION: Journal of the Institute of Navigation
(Your Name) thought you would like to see the NAVIGATION: Journal of the Institute of Navigation web site.
Citation Tools
A collocation framework to retrieve tropospheric delays from a combination of GNSS and InSAR
Endrit Shehaj, Karina Wilgan, Othmar Frey, Alain Geiger
NAVIGATION: Journal of the Institute of Navigation Dec 2020, 67 (4) 823-842; DOI: 10.1002/navi.398

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
Share
A collocation framework to retrieve tropospheric delays from a combination of GNSS and InSAR
Endrit Shehaj, Karina Wilgan, Othmar Frey, Alain Geiger
NAVIGATION: Journal of the Institute of Navigation Dec 2020, 67 (4) 823-842; DOI: 10.1002/navi.398
Twitter logo Facebook logo Mendeley logo
  • Tweet Widget
  • Facebook Like
  • Google Plus One
Bookmark this article

Jump to section

  • Article
    • Abstract
    • 1 INTRODUCTION
    • 2 TROPOSPHERIC DELAY IN MICROWAVE SIGNALS
    • 3 DATASETS
    • 4 GNSS-InSAR COMBINATION
    • 5 SIMULATED MEASUREMENTS: EVALUATIONS AND RESULTS
    • 6 COMBINATION OF REAL DATA
    • 7 DISCUSSION AND CONCLUSIONS
    • HOW TO CITE THIS ARTICLE
    • ACKNOWLEDGMENTS
    • Footnotes
    • REFERENCES
  • Figures & Data
  • Supplemental
  • References
  • Info & Metrics
  • PDF

Related Articles

  • No related articles found.
  • Google Scholar

Cited By...

  • No citing articles found.
  • Google Scholar

More in this TOC Section

  • GNSS L5/E5a Code Properties in the Presence of a Blanker
  • Robust Interference Mitigation in GNSS Snapshot Receivers
  • Identification of Authentic GNSS Signals in Time-Differenced Carrier-Phase Measurements with a Software-Defined Radio Receiver
Show more Original Article

Similar Articles

Keywords

  • GNSS < Atmospheric Effects
  • Radar < Alternatives and Backups to GNSS
  • Troposphere < Atmospheric Effects

Unless otherwise noted, NAVIGATION content is licensed under a Creative Commons CC BY 4.0 License.

© 2025 The Institute of Navigation, Inc.

Powered by HighWire