• DocumentCode
    1325983
  • Title

    Target detection in correlated SAR clutter

  • Author

    Blacknell, D.

  • Author_Institution
    Defence Evaluation & Res. Agency, Great Malvern, UK
  • Volume
    147
  • Issue
    1
  • fYear
    2000
  • fDate
    2/1/2000 12:00:00 AM
  • Firstpage
    9
  • Lastpage
    16
  • Abstract
    Synthetic aperture radar (SAR) clutter may be characterised by its single-point statistics and its correlation structure, both of which should be exploited in applications such as target detection. The non-Gaussian distributions associated with SAR clutter can be incorporated in detection schemes based on single-point statistics in a reasonably straightforward manner. However, use of the correlation structure is hampered by the difficulties associated with analytical manipulation of correlated non-Gaussian distributions. A generic model for correlated radar clutter is proposed based on a correlated Gaussian mixture distribution approximation to the clutter statistics in the log domain. Analytical manipulation of the model is possible because it is based on weighted sums of multivariate Gaussian distributions which have a tractable closed-form representation. The improved target detection performance which results from this approach is demonstrated
  • Keywords
    Gaussian distribution; correlation methods; radar clutter; radar detection; radar imaging; statistical analysis; synthetic aperture radar; SAR images; clutter statistics; correlated Gaussian mixture distribution approximation; correlated SAR clutter; correlated nonGaussian distributions; correlated radar clutter; correlation structure; generic model; log domain; multivariate Gaussian distributions; single-point statistics; synthetic aperture radar; target detection performance; tractable closed-form representation; weighted sums;
  • fLanguage
    English
  • Journal_Title
    Radar, Sonar and Navigation, IEE Proceedings -
  • Publisher
    iet
  • ISSN
    1350-2395
  • Type

    jour

  • DOI
    10.1049/ip-rsn:20000044
  • Filename
    838811