A multi-family GLRT for detection in polarimetric SAR images

L. Pallotta, C. Clemente, A. De Maio, D. Orlando

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

1 Citation (Scopus)
69 Downloads (Pure)


This paper deals with detection from multipolarization SAR images. The problem is cast in terms of a composite hypothesis test aimed at discriminating between the Polarimetric Covariance Matrix (PCM) equality (absence of target in the tested region) and the situation where the region under test exhibits a PCM with at least an ordered eigenvalue smaller than that of a reference covariance. This last setup reflects the physical condition where the back scattering associated with the target leads to a signal, in some eigen-directions, weaker than the one gathered from a reference area where it is apriori known the absence of targets. A Multi-family Generalized Likelihood Ratio Test (MGLRT) approach is pursued to come up with an adaptive detector ensuring the Constant False Alarm Rate (CFAR) property. At the analysis stage, the behaviour of the new architecture is investigated in comparison with a benchmark (but non-implementable) and some other adaptive sub-optimum detectors available in open literature. The study, conducted in the presence of both simulated and real data, confirms the practical effectiveness of the new approach.

Original languageEnglish
Title of host publication2016 Sensor Signal Processing for Defence (SSPD)
Place of PublicationPiscataway, NJ.
Number of pages5
ISBN (Electronic)9781509003266
Publication statusPublished - 18 Oct 2016
Event6th Conference of the Sensor Signal Processing for Defence - Royal College of Surgeons, Edinburgh, United Kingdom
Duration: 22 Sep 201623 Sep 2016
Conference number: 6


Conference6th Conference of the Sensor Signal Processing for Defence
Abbreviated titleSSPD 2016
Country/TerritoryUnited Kingdom


  • constant false alarm rate
  • covariance matrix equality
  • multi-family generalized likelihood ratio test
  • polarimetric SAR images


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