【作者】 岑小林；

【导师】 毛建旭；

【作者基本信息】 湖南大学 ， 电路与系统， 2008， 硕士

【摘要】 干涉合成孔径雷达(InSAR)三维成像技术是新近发展起来的空间观测技术,它利用合成孔径雷达数据的相位信息提取地面目标的三维信息,具有全天时、全天候、大范围、空间分辨率高等优点,可以广泛应用于军事领域和国民经济建设当中。本文在总结InSAR技术发展历程的基础上,分析了InSAR系统的成像原理,介绍了系统的数据处理流程。二维相位解缠是InSAR数据处理流程中重要步骤之一,也是主要误差来源,无论是获取数字高程模型还是获取地表形变信息,其精确程度都高度依赖于有效的相位解缠。为了获得高精度的InSAR干涉测量结果,必须实现准确有效的相位解缠,所以有必要对InSAR相位解缠算法进行研究。本文深入研究了相位解缠的原理,在此基础上分析了实际解缠过程中存在的难点。在详细分析枝切法和区域增长法相位解缠的处理流程及优缺点的基础上,提出了一种基于支持向量机(SVM)的相位解缠算法。算法综合考虑像元与相邻像元的相位差、相位导数方差等属性特征,利用支持向量机优异的分类能力对干涉图像元进行准确的分类,对不同区域分别采取Itoh方法和区域增长的方法进行解缠。基于真实和模拟数据分别进行了实验,实验结果表明该方法与传统方法相比能够避免低质量区域解缠失败,高质量区域更准确,具有更好的鲁棒性,可以应用于大量数据的相位解缠。针对最小二乘算法能够有效实现全局解缠,但是存在对误差抑制不够导致整体解缠效果下降的问题,本文提出了一种质量图和残差点相结合的InSAR相位解缠算法。算法以干涉图中残差点的分布为依据,优化质量阈值的确定方法,将干涉相位图划分为高低质量区域,更好的指导加权最小二乘法权重的设置,实现相位解缠的顺利进行。实验结果表明,本文提出的方法减少了干涉图中有效信息的流失,并且指标明确,人工干预少,解缠结果准确有效。本文最后研究了使用网络规划理论进行相位解缠的原理,实现了基于最小网络费用流的相位解缠算法。该算法对干涉相位图建立网络模型,将相位解缠的最小化问题转化为求网络最小费用问题,利用网络规划理论中成熟高效的算法求解。实验结果表明该算法获得了理想的解缠效果。更多还原

【Abstract】 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.更多还原