• DocumentCode
    3691178
  • Title

    Compressive sensing for neutrospheric water vapor tomography using GNSS and InSAR observations

  • Author

    Marion Heublein;Xiao Xiang Zhu;Fadwa Alshawaf;Michael Mayer;Richard Bamler;Stefan Hinz

  • Author_Institution
    Remote Sensing Technology Institute, German Aerospace Center (DLR), Oberpfaffenhofen, Germany
  • fYear
    2015
  • fDate
    7/1/2015 12:00:00 AM
  • Firstpage
    5268
  • Lastpage
    5271
  • Abstract
    This paper presents the innovative Compressive Sensing (CS) concept for tomographic reconstruction of 3D neutrospheric water vapor fields using data from Global Navigation Satellite Systems (GNSS) and Interferometric Synthetic Aperture Radar (InSAR). The Precipitable Water Vapor (PWV) input data are derived from simulations of the Weather Research and Forecasting modeling system. We apply a Compressive Sensing based approach for tomographic inversion. Using the Cosine transform, a sparse representation of the water vapor field is obtained. The new aspects of this work include both the combination of GNSS and InSAR data for water vapor tomography and the sophisticated CS estimation: The combination of GNSS and InSAR data shows a significant improvement in 3D water vapor reconstruction; and the CS estimation produces better results than a traditional Tikhonov regulari-zation with l2 norm penalty term.
  • Keywords
    "Global Positioning System","Delays","Three-dimensional displays","Tomography","Sparse matrices","Compressed sensing","Meteorology"
  • Publisher
    ieee
  • Conference_Titel
    Geoscience and Remote Sensing Symposium (IGARSS), 2015 IEEE International
  • ISSN
    2153-6996
  • Electronic_ISBN
    2153-7003
  • Type

    conf

  • DOI
    10.1109/IGARSS.2015.7327023
  • Filename
    7327023