The Research On InSAR Phase-unwrapping Algorithms

Interferometric Synthetic Aperture Radar(InSAR)is an advanced space observation technique that have been developed in the last two decades or so. It can be used to extract 3D information of the earth surface or detect the deformation extent of the earth surface from the phase information of SAR data. InSAR has quite a lot of advantages compared with traditional remote sensing technique. For example, it can work without the limitation of time or weather, and it can observe a huge area very quickly.At the beginning of this paper, we look back the history of how InSAR developed in the last two decades, analyze some fundamental theory and give some description of the data processing procedure. Two-dimensional phase unwrapping is one of the most important steps of this flow, and also the main source of error. When you want to fetch Digital Elevation Model or the deformation of earth surface, you will find that their precision depends on successful phase unwrapping. So it is quite important to investigate InSAR phase unwrapping algorithms.Then we analyze the principals of phase unwrapping, introduced several traditional methods. From the bases of investigating the advantages and disadvantages of some path-following algorithms, such as Branch-Cut and Regional Growth, we bring forward a algorithm that utilize Support Vector Machine (SVM). In this algorithm, the phase-related information including phased difference, residue and phase derivate variance are utilized. All the pixels are first classified by means of SVM into two types: residue pixels and non-residue pixels. The non-residue region is then unwrapped by the modified Itoh method, while the residue region is unwrapped by a region-growth strategy. The algorithm is finally validated with the real and simulated interferograms. The experiment results show the proposed algorithm is more effective and reliable than some existing algorithms.As for the Weighted Least-squares algorithm, the extraction of the quality map and the determining of the quality threshold is a very important step. In this paper, we analyses the quality map and its usage, offer an algorithm which correlates quality map and residues. The algorithm optimizes the way to determine quality threshold based on the distribution of the residues. This method will determine the threshold mainly depending on the statistic of residues. According to the experiment results, this method is fast and efficient.At the end of this paper, we investigate a relatively new phase unwrapping algorithm: minimum cost network flow algorithm. This method changes the phase unwrapping problem into a kind of searching the minimum cost of a network which has mature and efficient methods in network theory. We proved the validation of this algorithm through experiments.