Abstract: Phase unwrapping is the key step in Digital Elevation Model extraction and Differential Interferometry of Interferometric Synthetic Aperture Radar (InSAR). When the terrain is steep or slope is larger, the unwrapping result is bad and causes error transmission using the existing Kalman Filter phase unwrapping algorithm. Considering this situation, this paper presents a Kalman Filter phase unwrapping algorithm based on topographic factors for InSAR. It can be implemented through the introduction of the input control variable associated with topographic factors to the state-space model of Kalman Filter. Owing to the fact that the interference fringes directly reflect the change of the terrain and local fringe frequency is closely related with the local terrain slope, we can use the local fringe frequency estimation as the input control variable. In the local frequency estimation, using two-dimensional Chirp-Z transform, we can quickly get better estimate of the results. In this paper, using simulated data and real InSAR data to do the experiment and compared with the conventional Kalman filter phase unwrapping algorithm, it can gain more reliable unwrapping result. It is verified that the proposed algorithm can effectively deal with the situation of steep terrain and larger slope.