相位梯度自聚焦算法在条带模式SAR中的应用

相位梯度自聚焦(PGA)算法是一种稳健的高分辨SAR相位校正方法，在SAR领域得到广泛应用。但PGA是对聚束模式成像提出的，不能直接用于条带模式。本文利用两种模式之间的内在联系，将条带模式SAR数据分块处理，等效成聚束模式数据。然后，用聚束照射SAR成保算法实现成像，此时就可以利用PGA完成各决于图像的自聚焦过程，最后将各于固体适当拼揍，从而实现条带模式SAR的PGA处理，外场数据的处理证实了本文方法的可行性，同时，分块处理条带SAR数据实现了聚束照射SAR与条带模式SAR成像算法上的统一。     

带距离徙动校正的压缩感知PFA成像方法

目的 极坐标格式算法（PFA）是合成孔径雷达（SAR）聚束模式下的一种高分辨率成像算法,方位向增加孔径长度带来了数据存储和传输的负担,利用压缩感知进行合成孔径雷达成像可以减小采样率,以前的研究往往认为图像是2维可分离的而忽略距离徙动的影响,造成了图像质量的下降。提出一种在方位向利用压缩感知处理的PFA成像算法,可以校正距离徙动,保证压缩感知成像的图像分辨率。方法 在方位向进行压缩感知处理的过程时,采用了随距离空间频率变化的傅里叶基。结果 该方法可以有效代替PFA处理过程中的方位向插值,消除距离徙动的影响,保证距离向和方位向的分辨率。结论 仿真和实测数据的处理结果证明了该方法的有效性。     

下视SAR数据3维表面重建

目的 合成孔径雷达(SAR)因成像方法、几何角度等原因使得采集到的数据具有稀疏性及残缺性,如果直接用其进行建模,不能真实地还原物体。针对下视SAR数据的特点,提出一种在建模过程中能够自动修补稀疏及残缺数据的重建方法。方法 首先引入大津法对3维SAR数据进行预处理,然后将2维图像分割方法中的Chan-Vese模型推广应用到下视SAR数据的表面重建中,在初始表面及轮廓指示函数的求取过程中引入距离函数和内积函数。结果 将本文方法与等值面抽取法的重建结果进行比较,本文方法在重建的过程中能够自动修补空洞,重建出的模型表面更加光滑,能更加真实地反映原物体的特征。结论 可以将本文方法推广应用到稀疏及残缺SAR数据的建模中。     

全极化合成孔径雷达影像地形纠正及其在雪冰制图中的应用

针对合成孔径雷达（SAR）影像由于地形起伏引起的图像畸变问题,文章提出了基于相干矩阵的全极化SAR影像地形纠正算法,并运用于雪冰制图。该方法首先采用距离多普勒模型建立SAR成像几何模型;然后利用全极化Cloude特征分解方法对全极化SAR图像进行融合,将融合后的SAR图像与模拟图像进行配准提高SAR影像几何定位精度;最后利用投影面积归一化和极化方位角移动补偿技术对地形引起的辐射畸变进行纠正。采用中国长江源区南部唐古拉山中段冬克玛底冰川区域的C波段Radarsat-2全极化SAR数据进行验证,配准模拟SAR和原始SAR影像的控制点方位向和距离向的均方根误差（RMSE）分别为7.765和14.586个像素;经过地形纠正后的地物分类精度达80%以上。结果表明：（1）该方法能够有效消除SAR影像中几何和辐射畸变的影响;（2）地形纠正后的SAR数据在雪冰制图中具有可行性。     

快速数字影像重建的2维/3维医学图像配准

目的 针对2D/3D医学图像配准过程中数字影像重建技术(DRR)生成图像和相似性程度测量两个步骤计算量大、耗时较长这一问题,提出了一种基于Bresenham直线生成算法改进的模式强度与梯度相结合的混合配准算法.方法 首先利用Bresenham直线生成算法原理改进传统光线投射算法(Ray-Casting),完成DRR图像的生成;其次模式强度与梯度相结合并引入多分辨率策略来降低相似性测度的计算复杂度;最终利用改进的鲍威尔优化算法对参数进行优化,完成整个配准过程.结果 实验结果表明,改进的混合配准算法与基于相关系数、互信息和模式强度的配准算法相比,配准效率大幅提升.模拟配准实验和临床配准实验完成时间分别为76.2 s和64.9 s,比传统配准算法效率提升3~6倍.结论 提出的算法在保证配准精度和高鲁棒性的前提下,大幅度地提高了2D/3D医学图像配准算法的运算速度,可以满足临床上精确引导手术进行的实时性要求.     

An exact wide field digital imaging algorithm

Abstract

A new imaging algorithm is presented for Synthetic Aperture Radar (SAR) that is exact in the sense that it is capable of producing a complex image with excellent geometrical, radiometrical and phase fidelity. No interpolations or significant approximations are required, yet the method accomplishes range curvature correction over the complete range swath. The key to the approach is a quadratic phase perturbation of the range linearly frequency modulated signals while in the range signal, azimuth frequency transform (Doppler) domain. Range curvature correction is completed by a phase multiply in the two-dimensional frequency domain. Other operations required are relatively conventional. The method is generalizable to imaging geometries encountered in squint and spotlight SAR, inverse SAR, seismics, sonar, and tomography.     

GPU支持的SAR影像几何校正大规模并行处理

目的几何校正(又称地理编码)是合成孔径雷达(SAR)影像处理流程中重要的一个步骤,具有一定的计算复杂度,需要用到几何定位模型。本文针对星载SAR影像,采用有理多项式系数(RPC)定位模型,提出了图形处理器(GPU)支持的几何校正大规模并行处理方法。方法该方法充分利用GPU计算资源强大及几何校正过程中每个像素处理步骤一致的特点,每次导入大量像素至GPU,为每个像素分配一个线程,每个线程执行有理函数计算、投影变换、插值采样等计算复杂度高的步骤,通过优化配置dim Grid和dim Block参数,提升GPU的并行性能。该方法通过分块处理实现SAR影像大幅面处理,且可适用于多个不同分块大小。结果实验结果显示其计算加速比为38 44,为全面客观地分析GPU并行处理的特点,还计算了整体加速比,通过多个实验分析影响整体加速性能的因素,提出大块读写提高I/O性能的优化方法。结论该方法形式简洁,通用性好,可适用于几乎所有的星载SAR影像、不同的影像幅面;且加速性能明显。     

基于跨接约束的高分辨率SAR 影像与光学影像配准

为了实现高分辨率SAR 影像与光学影像之间自动/半自动配准, 提出了一种新颖、稳健的匹配算法。算法首先利用仿射变换进行SAR 影像和光学影像粗匹配, 简化了整体算法的处理复杂度;然后利用影像边缘稳健性, 使用边缘提取算子分别对SAR 影像和光学影像进行边缘提取, 为后续精匹配做好了数据准备; 最后使用基于边缘纹理跨接约束进行影像之间精匹配, 方法引入了邻域配准约束机制, 很好的解决了经典匹配多峰值效应, 提高了算法稳健性和实用性。以国内机载高分辨率SAR 数据和SPOT 25 PAN 数据为例进行算法验证, 实验结果表明该算法能实现自动/半自动的高分辨率SAR 和光学影像之间的像素级配准。     

An improved motion compensation method for high resolution UAV SAR imaging

The polynomial and sinusoidal motion errors always exist in the unmanned aero vehicle （UAV） SAR due to the small size and low velocity of the platform, causing serious spectrum compressing/stretching and significant spectral replicas of the azimuth signal. The motion errors induce serious blurring of the SAR image and ＂ghost targets＂, and can hardly be precisely estimated by the conventional motion compensation （MOCO） method. In this paper, an improved MOCO method is proposed to estimate and eliminate the motion errors in the high resolution UAV SAR without high precision inertial navigation system （INS） data. The time domain range walk correction （RWC） operation in the coarse phase error estimation process of the proposed MOCO method is the key operation that ensures the estimation accuracy of the whole MOCO method. Finally, the validity of the improved MOCO method is verified by computer simulations and real UAV SAR data processing.     

Effect of Digital Elevation Model resolution on topographic correction of airborne SAR

Topography in high relief mountainous areas may mask the signal variation in airborne Synthetic Aperture Radar (SAR) data caused by soil moisture, surface roughness and vegetation. It also affects the quality of image calibration and registration. Good quality calibration and registration are required for the use of SAR in the estimation of soil water. To address the problem of topographic effects, the widely available standard 30m x 30m United States Geological Survey (USGS) Digital Elevation Model (DEM) has been incorporated into SAR calibration and registration programs. The topographic resolution of SAR imagery relative to the USGS DEM was examined by comparing the correlation between incident angle (theta) and SAR backscatter (sigma 0) in a high resolution DEM (mapped at 1:4800 and 1:600 from aerial photography for two small areas) to that in the USGS DEM (mapped at 1 24 000). We found that SAR resolved topographic features not resolved by the USGS DEM. Filtering and aggregation techniques were applied to reduce speckle, the apparent noise due to small topographic features resolved by SAR but not resolved by the USGS DEM, and the registration error. Increasing the filter window from 3 x 3 to 5 x 5 to 9 x 9 and the cell size from 6m x 12 m to 30m x 30m to 90m x 90m, reduced the unexplained variability in backscatter by 50%. However, there was considerable unexplained variability at all levels of filtering and aggregation. Aggregation to 90m x 90m cell size resulted in blurred or obscured surface features of hydrological interest. Filtering with a 9 x 9 window and resolution cell size of 30m x 30 m was found to be optimal in terms of the amount of variability explained and the kinds of landscape features retained. Even after applying filtering and aggregation techniques, the correlation between sigma 0 and theta for the high resolution DEM (r = 0.54) was much better than for the USGS DEM ( r = 0.36). Correction functions for the numerical estimation of terrain influence on the backscatter variation in the SAR image were derived using empirical imaging models. Topographic effects on sigma 0 were further reduced in the corrected images. However, even after correction there was considerable unexplained sigma0 variability, some of which could be attributed to major topographic features. Thus, landscape features other than theta need to be incorporated in topographic correction procedures.     

Range ambiguity suppression in a synthetic aperture radar using pulse phase coding and two-pulse cancellation

ABSTRACT

In the presence of range ambiguity, the synthetic aperture radar (SAR) systems suffer from image aliasing, which dramatically degrades the quality of SAR images. In this article, an easy-to-implement technique for range ambiguity suppression is investigated, which is based on phase coding in the transmit pulse dimension, referred to as pulse phase coding (PPC). By properly designing the PPC series, it is possible to discriminate the range ambiguous echoes from different range areas in the Doppler frequency domain. To further suppress the range ambiguous echo, a two-pulse cancellation (TPC)-based SAR imaging method is proposed, which improves the quality of SAR images in the presence of range ambiguity. The proposed two-pulse cancellation is performed followed by the azimuth compression. The simulation results demonstrate the effectiveness of the proposed method.     

An automatic optical and SAR image registration method with iterative level set segmentation and SIFT

Although optical image registration methods have been successfully developed over the past decades, the registration of optical and synthetic aperture radar (SAR) images is still a challenging problem in remote sensing. Feature-based methods are considered to be more effective for multi-source image registration. However, almost all of these methods rely on the feature extraction algorithms. In this article, a simultaneous segmentation and feature-based registration method based on an iterative level set and scale-invariant feature transform (ILS-SIFT) is proposed. The core idea consists of three aspects: (1) an iterative procedure that combines image segmentation and matching is proposed to avoid registration failure caused by poor feature extraction; (2) a uniform level set segmentation model for optical and SAR images is presented to segment conjugate features; and (3) an improved SIFT algorithm is employed to determine whether the registration was successful. Experimental results have shown the effectiveness and universality of the proposed method.     

基于外部DEM的InSAR图像配准方法研究

雷达图像的配准是进行雷达干涉测量(SAR Interferometry, InSAR)处理的关键,为了保证干涉相位图或形变相位图反映真实地面特性,需要雷达图像之间亚像元级精度的配准。首先综述了已有的基于外部DEM的InSAR图像配准方法的思路及其不足之处,并提出了一种全新的思路:以图像之间的相干性作为目标函数,利用搜索的方法实现了雷达成像方位向和距离向的最优时间常数的估计,从而实现雷达图像之间亚像元级配准;还进一步推导了数字高程模型(Digital Elevation Model, DEM)的误差对算法精度影响的一个更加严密的表示。结论表明,在利用精确轨道数据的情况下,美国航天飞机测地计划SRTM获得的地形数据的精度可以满足精确雷达图像配准的要求。结果表明,利用基于外部DEM算法配准雷达图像在山区和大的时间基线情况下要优于常规相干多项式配准方法,理论上可以达到百分之一个像素的配准精度。     

干涉合成孔径雷达成像技术研究

用SIR-C/X-SAR的X波段的原始数据,实现了真实数据下星载双航过InSAR的数字高度 地图。首先给出了一种新的解释InSAR三维成像原理的数学描述。该描述对成像关系做了合理近 似,与以前的一些描述相比具有如下优点:①把相位差与地表高度在距离线上直接联系在一起,清 晰地反映出它们之间的关系;②指明了基线对高度测量的有效贡献在于其在斜距垂直方向的投影 这一重要概念;③可用于对测高精度与部分成像参数之间的关系做理论分析;④可用于求取相位差 值到地表高度值之间的转换系数;⑤基本反映了成像处理的实际过程;⑥可解释为何工程上可将相 位差与高度之间近似看成线性关系。然后,给出了一个完整的实现数字高度地图的数据处理过程, 并将整个过程分成9个环节,逐一对各环节的目的和作用做了扼要说明。最后,给出了包括单视 SAR成像、干涉相位条纹、水平相差修正和干涉条纹的降噪滤波在内的处理过程中关键步骤的结 果,和最终的三维地貌成像结果。     

Wavelet-based image registration technique for high-resolution remote sensing images

Image registration is the process of geometrically aligning one image to another image of the same scene taken from different viewpoints at different times or by different sensors. It is an important image processing procedure in remote sensing and has been studied by remote sensing image processing professionals for several decades. Nevertheless, it is still difficult to find an accurate, robust, and automatic image registration method, and most existing image registration methods are designed for a particular application. High-resolution remote sensing images have made it more convenient for professionals to study the Earth; however, they also create new challenges when traditional processing methods are used. In terms of image registration, a number of problems exist in the registration of high-resolution images: (1) the increased relief displacements, introduced by increasing the spatial resolution and lowering the altitude of the sensors, cause obvious geometric distortion in local areas where elevation variation exists; (2) precisely locating control points in high-resolution images is not as simple as in moderate-resolution images; (3) a large number of control points are required for a precise registration, which is a tedious and time-consuming process; and (4) high data volume often affects the processing speed in the image registration. Thus, the demand for an image registration approach that can reduce the above problems is growing. This study proposes a new image registration technique, which is based on the combination of feature-based matching (FBM) and area-based matching (ABM). A wavelet-based feature extraction technique and a normalized cross-correlation matching and relaxation-based image matching techniques are employed in this new method. Two pairs of data sets, one pair of IKONOS panchromatic images from different times and the other pair of images consisting of an IKONOS panchromatic image and a QuickBird multispectral image, are used to evaluate the proposed image registration algorithm. The experimental results show that the proposed algorithm can select sufficient control points semi-automatically to reduce the local distortions caused by local height variation, resulting in improved image registration results.     

利用高分辨率SAR立体像对提取数字地形模型研究

高分辨率的SAR卫星都具有多角度的扫描能力,使其同样具有立体观测的能力,为我们提供了另一种产生DEM的手段。利用SAR立体像对提取DEM的影响因子包括:数据类型斜距和地距、控制点和连接点、分辨率和相关器以及噪声和数据深度等。本文利用在两个地区的五景SAR像对就生成DEM和这些因子对DEM的影响进行了研究。通过研究发现TerraSAR-X和CosmoSkymed同样具有很好的立体成像能力,可以用来提取数字地形模型。适合利用其他手段生成DEM困难的地区使用。     

A novel Scan SAR imaging method for maritime surveillance via Lp regularization

In this article, a novel Scan mode synthetic aperture radar (SAR) imaging method for maritime surveillance is presented. Conventional Scan SAR is generally operated with severe azimuth resolution loss in order to cover a large area. The proposed imaging method changes the way Scan SAR illuminates sub-scenes and presents a new radar illuminating strategy based on ships’ spatial distribution in each sub-scene. To gain ships’ spatial distribution, a scene sensing algorithm based on radar range profiles together with a peak-seeking and clustering algorithm is introduced. After that, a Markov transfer-probability matrix is generated to make sure that radar illuminates each sub-scene randomly under the probability we calculated before. Finally, an imaging algorithm within the L_p (0 < p ≤ 1) regularization framework is utilized to reconstruct each sub-scene; the regularization problem is solved by an improved iterative thresholding algorithm. The whole wide swath image is joined by putting all the sub-scenes together. Experimental results support that the proposed imaging method can perform high-resolution wide swath SAR imaging effectively and efficiently without reducing the image resolution.     

SAR imaging by ω—κ migration

Abstract

A new method of processing synthetic aperture radar (SAR) data was originally developed by a group of geophysicists, who use seismic migration to generate seismic images of the Earth. Called here ω—κ migration, it has several advantages over more traditional methods of forming SAR images; they all arise because this method provides a mathematically exact solution to the imaging problem, in that the emitted waves are not being treated as plane waves. This paper discusses how migration processing can be applied to chirped radars; how it applies to spotlight data; and how to correct for non-uniform motions of the SAR platform.     

机载SAR实时成像系统自聚焦方法研究

发展我国自主产权的机载SAR（合成孔径雷达）实时成像系统，对于军事国防、资源探测、灾害预报等领域均具有重要的意义，在SAR成像算法中，自聚焦的好坏是影响图像分辨率的关键因素，但是因为自聚焦算法的复杂性，国内目前尚未有效地解决它在实时环境中的实现问题，从而使得实时成像的质量比较差，提出了一种利用GPS（全球定位系统）数据改善机载SAR实时成像系统自聚焦性能的实现方法，并在自主研制的机载SAR实时成像系统上实现，使该系统的成像分辨率得到明显改善。     

高分辨TerraSAR-X 图像舰船目标几何参数提取方法

准确提取SAR图像舰船目标几何参数是实现舰船分类的基础。由于SAR特有的成像机理, SAR图像旁瓣效应和方位模糊严重影响了舰船目标的几何参数估计,为此提出一种基于迭代线性回归的舰船几何参数提取方法。首先通过线性回归提取目标的主轴方位;然后利用循环迭代剔除远离主轴的虚假目标像素;最后用实测SAR数据进行了验证。实验结果表明,该算法对高分辨率的SAR舰船目标切片具有较好的参数估计效果。