InSAR phase unwrapping using nonlinear Kalman smoother

Phase unwrapping (PU) is one of the key processing step in reconstructing the digital elevation model (DEM) of a scene from interferometric synthetic aperture radar (InSAR) data. The PU problem entails the estimation of an absolute phase from the observation of its noisy principal (wrapped) values. This paper presents a 2D InSAR phase unwrapping algorithm exploiting the capability of the Kalman algorithm to simultaneously perform noise filtering and phase unwrapping. The performance of the proposed algorithm is tested on simulated InSAR images of the Gaussian type proving the effectiveness of our method.