• DocumentCode
    885012
  • Title

    Texture and speckle in high resolution synthetic aperture radar clutter

  • Author

    Posner, Fred L.

  • Author_Institution
    MIT Lincoln Lab., Lexington, MA, USA
  • Volume
    31
  • Issue
    1
  • fYear
    1993
  • fDate
    1/1/1993 12:00:00 AM
  • Firstpage
    192
  • Lastpage
    203
  • Abstract
    A theoretical model of high-resolution synthetic aperture radar (SAR) clutter that is able to predict the statistical effects of spatial averaging upon homogeneous clutter that is speckled and spatially correlated is discussed. The predictions of this model, when the texture correlation was assumed to be Gaussian-shaped, were found to be in excellent agreement with experimental results using grass clutter seen through a high-resolution radar. The predictions of this model, when the texture correlation was assumed to be exponential-shaped with a slant-range cosine factor, were found to be in excellent agreement with experimental results using tree clutter seen through a high-resolution radar. The use of an exponential shape, rather than a Gaussian shape, was necessary in order to achieve the more gradual decay in spatial correlations observed with tree clutter. The use of a slant-range cosine factor was necessary in order to achieve the negative correlations that were observed with tree clutter in the slant-range, but not the cross-range, dimension
  • Keywords
    geophysical techniques; image texture; radar clutter; radar theory; remote sensing by radar; speckle; synthetic aperture radar; SAR; geophysics; grass; high resolution synthetic aperture radar clutter; land surface; land surface imaging; measurement; remote sensing; slant-range cosine factor; spatial averaging; spatially correlated; speckle; technique; texture correlation; theoretical model; tree; vegetation; Layout; Predictive models; Radar clutter; Radar scattering; Rayleigh channels; Rayleigh scattering; Shape; Spatial resolution; Speckle; Synthetic aperture radar;
  • fLanguage
    English
  • Journal_Title
    Geoscience and Remote Sensing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0196-2892
  • Type

    jour

  • DOI
    10.1109/36.210460
  • Filename
    210460