The Research Of Phase Unwrapping For Interferometric Synthetic Aperture Radar

Interferometric synthetic aperture radar (InSAR) measures the height of the object based on the distance difference reflected by the absolute phase difference of the corresponding pixels on two pieces of synthetic aperture radar (SAR). But in fact, the phase difference is restricted to (-π,π), and phase unwrapping become so difficulty because of the influence by noise and under sample and so on. Therefore as a key technique in interference synthetic aperture radar (InSAR) signal processing, the phase unwrapping has been the focus and difficulty of the research. This dissertation will focus on the phase unwrapping in interference synthetic aperture radar (InSAR) signal processing, the main research work summarized as follows:1) The branch-cut method is one of the most important approaches for the phase unwrapping, and this dissertation, an improved branch-cut method is proposed based on the Goldstein branch-cut method. The positive and the negative residues in the interference image are combined in this method, then re-combined and replaced using the length of the branch-cut as criteria, so as to reduce the overall length of the branch-cut gradually and overcome the "isolated island phenomenon" in the unwrapping process effectively.2) To improve the processing precision of phase unwrapping in interferometric synthetic aperture radar (InSAR), the phase difference is replaced by local frequency estimation in this dissertation. The local frequency estimation can reflect topographic change more accurately than phase difference. To prevent the residues error spread all over the image, the mesh-less method is also introduced, which can avoid error propagation effectively by dividing local support domain in interferogram.3) A hybrid phase unwrapping method that combines the improved branch-cut method and surface-fitting method is proposed in this dissertation, the method applies different methods in different quality regions to unwrap the phase. It first uses the improved branch-cut method to unwrap the phases in high quality regions for the benefit of high accuracy; then uses surface-fitting method to fit the phases in low quality regions; finally, optimize the coefficients of the surface-fitting function using gene algorithm to obtain the unwrapped phase. The method can avoid the "isolated island phenomenon" of the branch-cut algorithm and the phase gradient error in the least-mean-square algorithm.4) A robust phase unwrapping method that based on total least mean square (TLMS) is proposed in this dissertation. Firstly practicability of the method can be proved in theory, and the computational efficiency also can be illustrated by some simulated data. The proposed algorithm is especially appealing due to its computational efficiency, and can improve the signal to noise ratio (SNR) of Interferogram.