Blind Source Separation in Polarimetric SAR Interferometry

Gabriel Vasile (1) , Leandro Pralon (1)

1 GIPSA-SIGMAPHY - GIPSA - Signal Images Physique

Polarimetric incoherent target decomposition aims in access-ing physical parameters of illuminated scatters through the analysis of target coherence or covariance matrix. In this framework, Independent Component Analysis (ICA) was recently proposed as an alternative method to Eigenvector decomposition to better interpret non-Gaussian heterogeneous clutter (inherent to high resolution SAR systems). Until now, the two main drawbacks reported of the aforementioned method are the greater number of samples required for an unbiased estimation, when compared to classical Eigenvector decomposition and the inability to be employed in scenarios under Gaussian clutter assumption. First, a Monte Carlo approach is performed in order to investigate the bias in estimating the Touzi Target Scattering Vector Model (TSVM) parameters when ICA is employed. A RAMSES X-band image acquired over Brétigny, France is taken into consideration to investigate the bias estimation under different scenarios. Finally, some results in terms of POLinSAR coherence optimization [1] in the context of ICA are proposed.

Mots clés: SAR; Polarimetry; Interferometry; ICA

Domaines: Traitement du signal et de l'image [eess.SP]

Gabriel Vasile, Leandro Pralon. Blind Source Separation in Polarimetric SAR Interferometry. IGARSS 2016 - IEEE International Geoscience and Remote Sensing Symposium, Jul 2016, Beijing, China. pp.4. ⟨hal-01387500⟩