• DocumentCode
    576196
  • Title

    Compressive sampling in SAR tomography: Results on COSMO-Skymed data

  • Author

    Barilone, Domenico ; Budillon, Alessandra ; Schirinzi, Gilda

  • Author_Institution
    Dipt. per le Tecnol., Univ. di Napoli Parthenope, Naples, Italy
  • fYear
    2012
  • fDate
    22-27 July 2012
  • Firstpage
    475
  • Lastpage
    478
  • Abstract
    SAR tomography allows the three-dimensional (3D) reconstruction of the reflectivity profile of the observed scene on the ground. It is based on the acquisition of several images of the same scene, collected with different view angles along slightly different orbits of the SAR platform. The spatial resolution in the elevation direction obtained with conventional Fourier-type techniques is related to the overall baseline extent of the acquisition orbits. Recently a tomographic technique denoted as Compressive Sampling Tomography (CST) has been introduced. It allows a drastic reduction of the number of acquisitions required and attains an increased resolution in the elevation direction. It exploits the sparsity property of the reflectivity profile in the elevation direction. In this paper some results obtained by applying CST to COSMO-Skymed real data are presented.
  • Keywords
    geophysical image processing; geophysical techniques; image reconstruction; radar imaging; synthetic aperture radar; COSMO-Skymed real data; Fourier-type techniques; SAR platform; SAR tomography; compressive sampling; compressive sampling tomography; image acquisition; reflectivity profile; three-dimensional reconstruction; tomographic technique; Azimuth; Image reconstruction; Image resolution; Reflectivity; Synthetic aperture radar; Tomography; Vectors; Compressive Sampling; Super-resolution imaging; Synthetic Aperture Radar Tomography;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Geoscience and Remote Sensing Symposium (IGARSS), 2012 IEEE International
  • Conference_Location
    Munich
  • ISSN
    2153-6996
  • Print_ISBN
    978-1-4673-1160-1
  • Electronic_ISBN
    2153-6996
  • Type

    conf

  • DOI
    10.1109/IGARSS.2012.6351383
  • Filename
    6351383