• DocumentCode
    3371191
  • Title

    SAR complex image analysis: A Gauss Markov and a multiple sub-aperture based target characterization

  • Author

    Singh, Jagmal ; Soccorsi, Matteo ; Datcu, Mihai

  • Author_Institution
    German Aerosp. Center (DLR), Wessling, Germany
  • fYear
    2010
  • fDate
    25-30 July 2010
  • Firstpage
    1585
  • Lastpage
    1588
  • Abstract
    In this paper we discuss Gauss-Markov Random Field (GMRF) based on multiple sub-aperture decomposition method for the analysis of targets in complex-valued high-resolution SAR data. Gauss-Markov Random Field (GMRF) model with a quadratic energy function as a parametric analysis parameterizes the spectogram of the signal, whereas sub-aperture decomposition method exploits the holographic property of the spectrum at the cost of reducing resolution. This analysis helps to understand, characterize and analyze complex-valued SAR data and provides temptation to use complex-valued SAR data over detected data.
  • Keywords
    Gaussian processes; Markov processes; radar imaging; random processes; synthetic aperture radar; GMRF; Gauss-Markov random field; SAR complex image analysis; complex-valued SAR data; high-resolution SAR data; holographic property; multiple sub-aperture based target characterization; multiple sub-aperture decomposition method; quadratic energy function; Analytical models; Apertures; Azimuth; Band pass filters; Computational modeling; Data models; Pixel; Gauss-Markov Random Field; Information Extraction; Single Look Complex; Sub Aperture Decomposition; Time Frequency Analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Geoscience and Remote Sensing Symposium (IGARSS), 2010 IEEE International
  • Conference_Location
    Honolulu, HI
  • ISSN
    2153-6996
  • Print_ISBN
    978-1-4244-9565-8
  • Electronic_ISBN
    2153-6996
  • Type

    conf

  • DOI
    10.1109/IGARSS.2010.5653827
  • Filename
    5653827