Analyse Temps-Fréquence appliquée à l'imagerie SAR polarimétrique

This paper deals with the analysis of the non-stationary behavior of scatterers in polarimetric SAR imaging . A method based on continuous wavelet and incoherent polarimetric decompositions is proposed to extract the polarimetric timefrequency signatures of scatterers. These signatures characterize scatterers according to their polarimetric /or energetic behavior versus the emitted frequency and the observation angle. Then, signatures from reference targets are used to train a multi-layer perceptron (MLP). All in all, SAR imaging data are classified by the MLP. The efficiency of this method is demonstrated, for the deterministic targets (manmade targets). It can be explained by the fact that the manmade targets present a strong non-stationary behavior. But for the vegetation and canopy the results are not convincing. It can be interpreted by the fact that the behavior of vegetation is stationary.