Statistical approaches for multichannel phase unwrapping

Synthetic Aperture Radar Interferometry allows the generation of Digital Elevation Model of an observed scene exploiting the phase signal. In order to provide the 3D reconstruction, a phase unwrapping procedure is required, which is an ill-posed problem. Multichannel datasets are able to solve the ambiguity providing a global solution. Within this manuscript two recently proposed statistical multichannel phase unwrapping methods are considered and compared. The first one is developed in the Bayesian-Markovian framework, while the second one is based on Kalman filtering. Results and comparisons on a simulated data set are reported, showing interesting results.