InSAR Kalman Filter phase unwrapping algorithm based on topographic factors

Abstract

Phase unwrapping is the key step in Digital Elevation Model extraction and the measurement of surface deformation of Interferometric Synthetic Aperture Radar (InSAR). When in steep terrain or larger slope, the unwrapping result is bad and causes error transmission using the existing Kalman Filter phase unwrapping algorithm. Considering this situation, this paper presents an improved 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, the local fringe frequency estimation can be used as the input control variable. In the local frequency estimation, using two-dimensional Chirp-Z transform, better estimate of the results may be quickly get. In this paper, using simulated data and real InSAR data to do the experiment, it can gain more reliable result compared with the conventional Kalman filter phase unwrapping algorithm. It is verified that the proposed algorithm can effectively deal with the situation of steep terrain and larger slope.