星载干涉合成孔径雷达若干关键技术的算法研究
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摘要
干涉合成孔径雷达是近年来新发展起来的一项微波遥感技术,它能够全天候、大范围、高精度地测量三维地形图(digital evaluation map,DEM)和地形形变,被广泛地应用于地形测绘、植被分类、人工建筑三维重建以及火山活动、冰川移动、地表沉降等有关地质动力学的研究。它对同一地区具有微小差别的两幅单视复数图像(single look complex,SLC)进行干涉处理,经过配准、滤波、解缠、去除平地效应等一系列的处理环节,最终获取三维DEM或地表形变的信息。本文工作主要集中于InSAR数据处理中的两个关键技术:SLC图像配准和相位解缠,同时,提出了一种构造不同图像质量的模拟SLC图像的方法。
论文首先介绍了合成孔径雷达干涉测量三维地形和地表形变的发展历程,概述了国内外的InSAR技术发展以及当前的研究状况,详细地论述InSAR技术反演DEM的处理过程,并对每个InSAR处理环节的原理和主要算法进行了阐述和总结。
本文采用了一种由粗配准到精配准的两级配准策略,以两幅图像对应像素的强度平均平方差函数作为相似性测度,对两幅SLC图像进行配准,配准精度达到了亚像素级。该方法首先根据两图像中特征明显的区域,粗略选取相同区域。经过过采样后,在副图像上选取几十个256×256的搜索窗口,依据最小平均平方差函数进行粗配准。方位向滤波后,在副图像上均匀选取几百个64×64的窗口,对主副图像做间隔为0.1像元的插值后,再以最小平均平方差函数进行精配准。设定阈值选取可靠的控制点,经过一致性检测后,根据这些控制点,由二维多项式拟合方程计算出主副图像上对应像素间的配准关系。最后,采用升余弦插值核进行插值,计算副图像各像素的偏移。将配准后的两幅ENVISAT图像进行干涉和滤波处理,干涉图像出现的清晰干涉条纹证明了本文配准算法的有效性。
本文提出了一种基于蚁群算法的路径跟踪相位解缠算法。该方法考虑了整体的枝切线长度最短,通过蚁群算法,生成较短的全局路径。再把全局路径分割为多条“极性平衡”的路径,使得生成的总路径更短。在避开路径进行相位积分时,由路径引起的解缠误差更小,也不会形成孤立的不解缠区域,提高了相位解缠的精度。同时,该方法有很好的并行性,利用并行计算机计算能够大大加快运算速度。将该算法分别应用于仿真SLC数据的干涉图像和ENVISAT-ASAR伊朗Bam地区的InSAR图像,并与其他几种解缠算法作了比较。实验结果表明:该算法可有效用于不同复杂地形的干涉图像的相位解缠。与其他几种解缠算法相比,其解缠精度高,解缠速度也较快。
针对大尺度密集残差点干涉图像的相位解缠,本文提出了两种路径跟踪相位解缠算法:区域分片连接法以及中心扩展搜索法。前者先将干涉图像分割成多片极性平衡区域,然后按照最近距离原则连接每片区域的异性残差点并建立枝切线。后者由图像中心向外逐步扩展,建立搜索窗口,搜索并连接最近距离的异性残差点。前者适用于残差点分散地分布在多片极性平衡区域的干涉图像,后者适用于残差点密集均匀分布的干涉图像。它们建立的枝切线较短,避免了残差点的多次连接,且提高了解缠精度。实验结果表明,本文提出的两种算法具有解缠精度高,运算速度快等优点。尤其适用于尺寸较大、残差点较密集的干涉图像。
本文提出了一种构造不同质量的SLC图像的方法。用中国广东地区的DEM数据和ENVISAT-ASAR的参数,按SAR投影成像和双尺度粗糙面散射计算,构造了SLC数据的相位和幅值。通过有比例地变更DEM的起伏程度生成多景具有不同的起伏高度和阴影的SLC图像,进而构造了多景不同残差点数量的相干数据。该数据能够对各种InSAR解缠算法进行有效的估评检验,有助于分析实际中的SAR图像的阴影对InSAR反演误差的影响。
Interferometric Synthetic Aperture Radar(InSAR) is a new developed microwave remote sensing technique.It is known by its unique advantage of all-weather,large-region monitoring and high-resolution imaging for the measurement of 3D DEM and earth surface deformation.InSAR has been applied widely in topography mapping,vegetation classification,3D reconstruction of artificial buildings and geodynamics related research such as surface subsidence,volcano and iceberg activity etc.3D DEM and earth surface deformation can be retrieved from two single look complex(SLC) image with minor difference after a processing chain of registration,filtering, interference and phase unwrapping etc.This dissertation mainly focuses on two key steps in InSAR data processing:SLC images registration and phase unwrapping.In addition,a method which is used to simulate SLC images with different quality is proposed.
Firstly,the history developing of InSAR,especially the retrieval of DEM by InSAR,is reviewed,and the current situation of InSAR research in domestic and abroad is depicted briefly in this dissertation.The theory and conventional algorithms of InSAR processing steps are summarized and discussed.
The development of InSAR DEM retrieval and the current situation of InSAR research in domestic and abroad are reviewed firstly.And then the theory and conventional algorithms of InSAR processing steps are summarized and discussed.
A coarse-to-fine registration framework,based on the mean square difference(MSD) function,is introduced in this dissertation.Many windows whose size is 256×256 are chosen equally and the coarse offsets of windows in slave image are determined when the MSD function of every window reaches its minimum.After filtering out the nonoverlap spectrum in azimuth,hundreds of windows whose size are 64×64 and disperse equally on slave image are used to measure subpixel shifts.Taking the similar step as coarse registration processing,fine registration determines subpixel shifts by moving windows with 0.1 pixel interval.The centers of those moving windows with higher similarity are chosen as control points for next step registration.The corresponding relation between the two images is computed from 2D-polynomial transformation model of those selected control points.After the slave image is interpolated with Raise Cosine kernel,offset of each subpixel in slave image relative to the corresponding pixels in master image is obtained. According to the offsets,the entire slave image is resampled and registered with the master image.The experimental results,showing clear fringes,verify the validity the registration procedure.
A new approach based on Ant Colony Optimization(ACO) is presented to show good feasibility for phase unwrapping of the DEM retrieval.This approach seeks the shortest path linking all residues via ACO algorithm and then divides it into segments of balanced residues,in order to avoid isolated regions which can not be unwrapped.Due to the optimization strategy to establish the branch cuts,the unwrapping error can be reduced significantly.Experiments of simulated dataset and real ENVISAT data are employed to test the proposed approach.The unwrapping results indicate that ACO algorithm is an optional compromise strategy between preferable unwrapping precision and less time consuming.
Aiming at interferograms with large size and dense residues,two path-following unwrapping algorithms which are suitable for different distribution of the dense residues are presented:the method of multi-patches connecting opposite residues and the method of center expanded searching opposite residues.The idea of the former is to segment the interferogram into many balanced patches according to the minimum distance principle of opposite residues,whereas the latter method is to search and connect the nearest neighbor opposite residues beginning from the center region of the interferogram to its boundary.The former is appropriate for interferograms whose residues disperse in many patches and the latter suits for interferograms whose residues are well-distributed as a whole.They improve the unwrapping accuracy for they avoid repetitive connection of residues and longer branch cuts.The algorithms are employed to ENVISAT datasets,clearly demonstrating their tangible improvement on unwrapping accuracy over other path-following unwrapping algorithms.Experimental results show that the two methods,which are applicable for interferograms with dense residues dispersing differently, have the advantages in execution time and precision.
A SLC image simulation method is presented in this dissertation.Based on the SAR imaging principle and scattering model of two-scale rough surface, the amplitude and phase of the SLC image is computed from the real DEM under the orbit parameters of ENVISAT-ASAR.Several sets of SLC images with different shadow are simulated by changing the differently scaled DEM and then interferograms with different residues are generated from the simulated SLC images,which can be used to verify the InSAR algorithm and analyze the influence of InSAR shadow.
论文首先介绍了合成孔径雷达干涉测量三维地形和地表形变的发展历程,概述了国内外的InSAR技术发展以及当前的研究状况,详细地论述InSAR技术反演DEM的处理过程,并对每个InSAR处理环节的原理和主要算法进行了阐述和总结。
本文采用了一种由粗配准到精配准的两级配准策略,以两幅图像对应像素的强度平均平方差函数作为相似性测度,对两幅SLC图像进行配准,配准精度达到了亚像素级。该方法首先根据两图像中特征明显的区域,粗略选取相同区域。经过过采样后,在副图像上选取几十个256×256的搜索窗口,依据最小平均平方差函数进行粗配准。方位向滤波后,在副图像上均匀选取几百个64×64的窗口,对主副图像做间隔为0.1像元的插值后,再以最小平均平方差函数进行精配准。设定阈值选取可靠的控制点,经过一致性检测后,根据这些控制点,由二维多项式拟合方程计算出主副图像上对应像素间的配准关系。最后,采用升余弦插值核进行插值,计算副图像各像素的偏移。将配准后的两幅ENVISAT图像进行干涉和滤波处理,干涉图像出现的清晰干涉条纹证明了本文配准算法的有效性。
本文提出了一种基于蚁群算法的路径跟踪相位解缠算法。该方法考虑了整体的枝切线长度最短,通过蚁群算法,生成较短的全局路径。再把全局路径分割为多条“极性平衡”的路径,使得生成的总路径更短。在避开路径进行相位积分时,由路径引起的解缠误差更小,也不会形成孤立的不解缠区域,提高了相位解缠的精度。同时,该方法有很好的并行性,利用并行计算机计算能够大大加快运算速度。将该算法分别应用于仿真SLC数据的干涉图像和ENVISAT-ASAR伊朗Bam地区的InSAR图像,并与其他几种解缠算法作了比较。实验结果表明:该算法可有效用于不同复杂地形的干涉图像的相位解缠。与其他几种解缠算法相比,其解缠精度高,解缠速度也较快。
针对大尺度密集残差点干涉图像的相位解缠,本文提出了两种路径跟踪相位解缠算法:区域分片连接法以及中心扩展搜索法。前者先将干涉图像分割成多片极性平衡区域,然后按照最近距离原则连接每片区域的异性残差点并建立枝切线。后者由图像中心向外逐步扩展,建立搜索窗口,搜索并连接最近距离的异性残差点。前者适用于残差点分散地分布在多片极性平衡区域的干涉图像,后者适用于残差点密集均匀分布的干涉图像。它们建立的枝切线较短,避免了残差点的多次连接,且提高了解缠精度。实验结果表明,本文提出的两种算法具有解缠精度高,运算速度快等优点。尤其适用于尺寸较大、残差点较密集的干涉图像。
本文提出了一种构造不同质量的SLC图像的方法。用中国广东地区的DEM数据和ENVISAT-ASAR的参数,按SAR投影成像和双尺度粗糙面散射计算,构造了SLC数据的相位和幅值。通过有比例地变更DEM的起伏程度生成多景具有不同的起伏高度和阴影的SLC图像,进而构造了多景不同残差点数量的相干数据。该数据能够对各种InSAR解缠算法进行有效的估评检验,有助于分析实际中的SAR图像的阴影对InSAR反演误差的影响。
Interferometric Synthetic Aperture Radar(InSAR) is a new developed microwave remote sensing technique.It is known by its unique advantage of all-weather,large-region monitoring and high-resolution imaging for the measurement of 3D DEM and earth surface deformation.InSAR has been applied widely in topography mapping,vegetation classification,3D reconstruction of artificial buildings and geodynamics related research such as surface subsidence,volcano and iceberg activity etc.3D DEM and earth surface deformation can be retrieved from two single look complex(SLC) image with minor difference after a processing chain of registration,filtering, interference and phase unwrapping etc.This dissertation mainly focuses on two key steps in InSAR data processing:SLC images registration and phase unwrapping.In addition,a method which is used to simulate SLC images with different quality is proposed.
Firstly,the history developing of InSAR,especially the retrieval of DEM by InSAR,is reviewed,and the current situation of InSAR research in domestic and abroad is depicted briefly in this dissertation.The theory and conventional algorithms of InSAR processing steps are summarized and discussed.
The development of InSAR DEM retrieval and the current situation of InSAR research in domestic and abroad are reviewed firstly.And then the theory and conventional algorithms of InSAR processing steps are summarized and discussed.
A coarse-to-fine registration framework,based on the mean square difference(MSD) function,is introduced in this dissertation.Many windows whose size is 256×256 are chosen equally and the coarse offsets of windows in slave image are determined when the MSD function of every window reaches its minimum.After filtering out the nonoverlap spectrum in azimuth,hundreds of windows whose size are 64×64 and disperse equally on slave image are used to measure subpixel shifts.Taking the similar step as coarse registration processing,fine registration determines subpixel shifts by moving windows with 0.1 pixel interval.The centers of those moving windows with higher similarity are chosen as control points for next step registration.The corresponding relation between the two images is computed from 2D-polynomial transformation model of those selected control points.After the slave image is interpolated with Raise Cosine kernel,offset of each subpixel in slave image relative to the corresponding pixels in master image is obtained. According to the offsets,the entire slave image is resampled and registered with the master image.The experimental results,showing clear fringes,verify the validity the registration procedure.
A new approach based on Ant Colony Optimization(ACO) is presented to show good feasibility for phase unwrapping of the DEM retrieval.This approach seeks the shortest path linking all residues via ACO algorithm and then divides it into segments of balanced residues,in order to avoid isolated regions which can not be unwrapped.Due to the optimization strategy to establish the branch cuts,the unwrapping error can be reduced significantly.Experiments of simulated dataset and real ENVISAT data are employed to test the proposed approach.The unwrapping results indicate that ACO algorithm is an optional compromise strategy between preferable unwrapping precision and less time consuming.
Aiming at interferograms with large size and dense residues,two path-following unwrapping algorithms which are suitable for different distribution of the dense residues are presented:the method of multi-patches connecting opposite residues and the method of center expanded searching opposite residues.The idea of the former is to segment the interferogram into many balanced patches according to the minimum distance principle of opposite residues,whereas the latter method is to search and connect the nearest neighbor opposite residues beginning from the center region of the interferogram to its boundary.The former is appropriate for interferograms whose residues disperse in many patches and the latter suits for interferograms whose residues are well-distributed as a whole.They improve the unwrapping accuracy for they avoid repetitive connection of residues and longer branch cuts.The algorithms are employed to ENVISAT datasets,clearly demonstrating their tangible improvement on unwrapping accuracy over other path-following unwrapping algorithms.Experimental results show that the two methods,which are applicable for interferograms with dense residues dispersing differently, have the advantages in execution time and precision.
A SLC image simulation method is presented in this dissertation.Based on the SAR imaging principle and scattering model of two-scale rough surface, the amplitude and phase of the SLC image is computed from the real DEM under the orbit parameters of ENVISAT-ASAR.Several sets of SLC images with different shadow are simulated by changing the differently scaled DEM and then interferograms with different residues are generated from the simulated SLC images,which can be used to verify the InSAR algorithm and analyze the influence of InSAR shadow.
引文
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