A novel Phase Unwrapping (PhU) technique for InSAR interferometric stacks based on statistical estimation theory is presented. The approach is intended for exploiting both amplitude and phase of the acquired data in order to express the multi-baseline likelihood function without the assumption of independence among channels, i.e. by considering the full mutual correlation matrix. Moreover, the contextual information is adopted for regularizing the solution, obtaining a Maximum A Posteriori (MAP) estimator. First results on real datasets related to an urban scenario are presented, showing the interesting performances of the proposed method in terms of Digital Elevation Model (DEM) reconstruction
A new phase unwrapping approach using mutually correlated multi-baseline interferograms
BASELICE, FABIO;FERRAIOLI, GIAMPAOLO;PASCAZIO, Vito;SCHIRINZI, Gilda
2014-01-01
Abstract
A novel Phase Unwrapping (PhU) technique for InSAR interferometric stacks based on statistical estimation theory is presented. The approach is intended for exploiting both amplitude and phase of the acquired data in order to express the multi-baseline likelihood function without the assumption of independence among channels, i.e. by considering the full mutual correlation matrix. Moreover, the contextual information is adopted for regularizing the solution, obtaining a Maximum A Posteriori (MAP) estimator. First results on real datasets related to an urban scenario are presented, showing the interesting performances of the proposed method in terms of Digital Elevation Model (DEM) reconstructionI documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
