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.