• DocumentCode
    2194202
  • Title

    Radar backscatter characterization approach combining global TanDEM-X data

  • Author

    Rizzoli, Paola ; Bräutigam, Benjamin

  • Author_Institution
    Microwaves & Radar Inst., German Aerosp. Center (DLR), Oberpfaffenhofen, Germany
  • fYear
    2012
  • fDate
    22-27 July 2012
  • Firstpage
    3305
  • Lastpage
    3308
  • Abstract
    Global radar backscatter data can be used for accurate performance estimation and instrument setting optimization for Synthetic Aperture Radar (SAR) systems, e.g. in the TerraSAR-X and TanDEM-X missions. Both missions offer global remote sensing data in order to characterize X-band backscatter by performing a statistical analysis on SAR image quicklooks. A new approach for the estimation of radar backscatter for any polarization, ground classification type and incidence angle is presented, recurring to the use of SAR data coming from the TanDEM-X mission. The introduction of topographical information on the illuminated ground area allows for the discrimination of backscatter samples which are not affected by shadowing and layover, increasing the reliability of the estimation approach. The analysis technique is presented, leading to the generation of a set of X-band backscatter models. First results, obtained using TanDEM-X SAR data, are introduced.
  • Keywords
    backscatter; radar imaging; remote sensing by radar; statistical analysis; synthetic aperture radar; SAR image quicklooks; SAR systems; Synthetic Aperture Radar; TanDEM-X mission; TerraSAR-X mission; backscatter samples; estimation approach; global TanDEM-X data; global remote sensing data; illuminated ground area; incidence angle; instrument setting optimization; layover; performance estimation; radar backscatter characterization approach; shadowing; statistical analysis; topographical information; Backscatter; Data models; Histograms; Remote sensing; Spaceborne radar; Synthetic aperture radar; SAR; TanDEM-X; TerraSAR-X; X-band; backscatter;
  • 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.2012.6350597
  • Filename
    6350597