Abstract
The problem of coherent multi-polarization SAR
change detection exploiting data collected from N multiple
polarimetric channels, is addressed in this paper. The change
detection problem is formulated as a binary hypothesis testing
problem and a special block-diagonal structure for the polarimetric
covariance matrix is forced to design a novel detector based
on the Generalized Likelihood Ratio Test criterion. It is shown
that the new decision rule ensures the Constant False Alarm Rate
(CFAR) property. At the analysis stage, results on both simulated
and real high resolution SAR data show the effectiveness of the
proposed decision rule and its superiority against the traditional
unstructured GLRT in some scenarios of practical interest.
change detection exploiting data collected from N multiple
polarimetric channels, is addressed in this paper. The change
detection problem is formulated as a binary hypothesis testing
problem and a special block-diagonal structure for the polarimetric
covariance matrix is forced to design a novel detector based
on the Generalized Likelihood Ratio Test criterion. It is shown
that the new decision rule ensures the Constant False Alarm Rate
(CFAR) property. At the analysis stage, results on both simulated
and real high resolution SAR data show the effectiveness of the
proposed decision rule and its superiority against the traditional
unstructured GLRT in some scenarios of practical interest.
| Original language | English |
|---|---|
| Publication status | Published - Oct 2014 |
| Event | International Radar Conference 2014 - Lille, France Duration: 13 Oct 2014 → 17 Oct 2014 |
Conference
| Conference | International Radar Conference 2014 |
|---|---|
| Country/Territory | France |
| City | Lille |
| Period | 13/10/14 → 17/10/14 |
Keywords
- SAR imaging
- change detection
- multipolarization