Multi-model CFAR detection in FOliage PENetrating SAR images

Alessio Izzo, Marco Liguori, Carmine Clemente, Carmelo Galdi, Maurizio Di Bisceglie, John J. Soraghan

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A multi-model approach for Constant False Alarm Ratio (CFAR) detection of vehicles through foliage in FOliage PENetrating (FOPEN) SAR images is presented. Extreme value distributions and Location Scale properties are exploited to derive an adaptive CFAR approach that is able to cope with different forest densities. Performance analysis on real data is carried out to estimate the detection and false alarm probabilities in the presence of a ground truth.
Original languageEnglish
Pages (from-to)1769-1780
Number of pages12
JournalIEEE Transactions on Aerospace and Electronic Systems
Issue number4
Early online date14 Mar 2017
Publication statusPublished - 31 Aug 2017


  • constant false alarm ratio
  • foliage penetrating
  • extreme value distributions
  • location scale
  • forest densities
  • vehicles detection
  • false alarm probabilities

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