New results in calculating the unambiguous phase for SAR interferometry

The paper presents a phase unwrapping algorithm based on a linearized extended Kalman filter. The Kalman filter exploits a so called `Basic-Slope Model', enabling the filter to incorporate additional information about the mean local phase variation. This phase variation will be estimated directly from the sample frequency spectrum of the interferogram by a local slope estimator. Additionally, the local slope estimator calculates the error variance of the estimated phase variation by using Fisher's information. The Kalman filter then fuses the information directly obtained from real and imaginary part of the interferogram with information from the local slope estimator. The paper outlines the principle operation of the phase unwrapping algorithm and explains the cooperation of the Extended Kalman filter with the local slope estimator. At last the efficiency of this phase unwrapping algorithm will be shown by simulations and real InSAR images.