一种基于重叠子孔径回波信息的SAR图像配准算法

合成孔径雷达（SAR）图像配准是寻找多幅SAR图像之间的几何变换关系的过程，使不同图像校正到统一空间坐标系。传统光学图像配准方法，如尺度不变特征变换（SIFT）结合随机抽样一致（RANSAC）用于SAR图像配准时，由于受到乘性相干斑噪声的干扰，配准性能受到较大影响。提出一种基于重叠子孔径回波信息的SAR图像配准算法，在对SAR回波复数据进行成像处理的过程中，利用相位信息并结合子孔径自聚焦方法得到强相关的重叠子孔径图像，并利用多图像配准方法实现成像孔径内和孔径间的子孔径图像配准，提高图像配准精度。多个不同场景的实测数据处理结果表明：所提算法相比于SIFT+RANSAC算法，同名点数量增加，误匹配点对减少，均方根误差减小，对相干斑噪声具有较强的鲁棒性，配准效果得到了显著提高。     

利用α稳定分布的小波域SAR图像降斑算法

提出了一种改进的合成孔径雷达(SAR)图像α-MAP降斑算法,通过采用厚尾α稳定分布和引入噪声方差调整系数的方法,可以获得更好的降斑和纹理保持效果,同时应用平稳小波分解来解决Gibbs效应引入的伪噪声问题。最后通过对实际SAR图像的降斑处理,对本文的算法与最新的小波软阈值算法以及传统的局部自适应滤波器在性能参数和滤波效果上做了全面的比较。试验表明本文的算法更具适应性,实现了降斑与纹理保持更有效的综合滤波,在性能参数和复原图像效果上都有较好的表现。     

一种平稳小波方向能量阈值滤波的SAR图像去噪方法

由于SAR图像相干斑噪声是非高斯分布的,无法直接采用光学成像系统的去噪技术处理,因此,目前还没有真正的理想算法广泛适用于SAR图像去噪.在分析目前流行的空频域去噪方法优缺点的基础上,提出了1种小波域SAR图像去噪方法.为了克服离散小波变换缺乏平移不变性及方向选择性受限的缺点,该方法利用平稳小波将图像分解为低频逼近信号和...     

一种用于条带模式SAR成像的自聚焦算法

 针对现有条带模式合成孔径雷达（SAR）成像的自聚焦算法中,相位的拼接会引起误差的严重积累,本文结合相位梯度自聚焦（PGA）算法和子孔径偏移（MD）算法,提出了一种新的用于条带模式SAR成像的自聚焦算法（PGA-MD）。该算法先利用PGA算法有效估计各子孔径相位误差函数,再利用相邻子图间方位向偏移量和线性相位之间的关系,通过MD算法精确估计相邻子图间方位向偏移量,然后计算线性相位差,并基于—阶导数实现子孔径相位误差函数拼接。理论分析以及实测数据处理结果对比均表明PGA-MD算法可以有效提高对条带SAR图像的自聚焦效果。     

方位降采样滤波器设计和FPGA实现

在SAR(合成孔径雷达)雷达实时信号处理中,为了降低运算量且不影响成象质量,通常需要对输入的距离-方向二维数据在方位上做降采样和滤波处理。为了满足实时处理的需要,本文提出了一种将降采样和方位滤波相结合的设计,以及利用窗函数设计滤波器系数的方法,运用硬件描述语言Verilog HDL构造了一种用现场可编程门阵列FPGA实现降采样滤波器的电路结构,并分析了其性能。该降采样滤波器的降采样率和滤波器阶数可变,可适应多种场合的需要。     

基于置信度加权的组合导航数据融合算法

 针对联邦滤波融合算法中由于模型量测噪声统计特性未能被准确描述导致其子滤波器误差变大，进而导致联邦滤波估计出现偏差的问题，为了改进联邦滤波融合方法，将模糊自适应卡尔曼滤波方法和置信度加权方法与联邦滤波融合方法相结合，应用于组合导航系统。该方法首先将模糊自适应卡尔曼滤波方法应用于各子滤波器，使其能够跟踪真实量测噪声统计特性。然后通过模糊方法计算得到各子滤波器的置信度，进而得到联邦滤波器的置信度，再由得到的置信度对各子滤波器及联邦滤波器输出进行加权，得到最终的全局输出。对车载组合导航系统的仿真结果表明，这种算法对量测噪声具有较强的自适应性，能够抑制置信度低的子滤波器在融合系统中所占的权重，提高联邦滤波融合算法的精度，是一种可行的车载组合导航数据融合算法。     

曲线轨迹下前视多通道SAR解模糊成像算法

前视合成孔径雷达（SAR）存在左右模糊问题，在直线航迹下，目标关于航线对称模糊，模糊关系不随航线变化，可利用波束形成进行全孔径解模糊处理；但在曲线航迹下，目标的模糊关系具有空变性，不能全孔径解模糊成像。针对这一问题，分析了曲线航迹下目标模糊关系的空变特性，提出一种前视多通道SAR快速后向投影子孔径处理解模糊成像算法。首先进行子孔径划分，在每个子孔径内目标的模糊关系近似不变，每个子孔径分别成像，然后通过波束形成对每幅子图像进行解模糊处理，最后融合子图像得到最终的成像结果。算法有效解决了曲线轨迹下目标模糊关系的空变性对解模糊的影响，仿真实验验证了算法的有效性。     

基于MAP估计和广义高斯分布的SAR图像边缘比率检测方法

 合成孔径雷达(SAR)图像的低信噪比和乘性相干斑噪声给SAR图像的边缘检测带来了极大的困难.通过引入广义高斯(GG)分布作为局部均值功率的先验分布模型,给出了局部均值功率在最大后验概率(MAP)意义下的最优估计,进而提出一种新的SAR图像边缘比率检测算子.利用以梅林变换为基础的对数累积量(MoLC)方法估计GG分布的参数,在此基础上给出一种局部均值功率MAP估计和GG分布参数估计的联合迭代求解方法.利用SAR实测数据对本文提出的边缘检测算子进行仿真验证,并将其与平均比率(RoA)算子和指数加权均值比(ROEWA)算子进行了对比,结果表明该算子可以有效克服相干斑噪声的影响,边缘定位准确且虚假边缘明显减少.     

基于小波域贝叶斯估计模糊萎缩的SAR图像降斑算法

提出了基于小波域高斯混合模型贝叶斯估计模糊萎缩的SAR图像降斑算法.该算法分析了SAR图像在平稳小波变换(SWT)域中的统计模型,并用高斯混合模型对其进行描述,推导出基于贝叶斯估计的信号最小均方误差(MMSE)的模糊萎缩因子.籍此再根据小波域相邻尺度间小波系数的相关性,采用分区域模糊萎缩思想,很好地得到无斑点真实信号小波系数的估计值.仿真结果表明该算法在大大抑制斑点噪声的同时,有效地保持了边缘,其性能优于改进Lee滤波、小波软阈值和SWT萎缩降斑算法.     

基于SAR图像匹配结果可信度评价的INS/SAR自适应Kalman滤波算法

在惯性导航系统（INS）/合成孔径雷达（SAR）组合导航系统中，SAR图像易受斑点噪声的影响，图像匹配的精度对整个导航系统精度的影响十分明显，能够准确地分析SAR图像匹配过程中的误差特性，利用有效的图像匹配信息辅助INS进行组合定位尤为重要。针对上述问题，在加权Hausdorff距离匹配算法的基础上，对影响SAR图像匹配精度的因素进行了分析，提出了一种基于模糊推理的匹配结果可信度评价准则，经过可信度筛选，将有效的匹配信息与INS进行组合；对合理范围内的匹配误差变化引起量测噪声统计特性发生变化，进而导致Kalman滤波精度下降的问题，研究采用改进的Sage-Husa自适应滤波算法对量测噪声方差阵进行动态调整，使其更加接近系统的当前状态。搭建仿真验证平台对所提算法进行了验证，结果表明，该算法能够在合理的匹配误差范围内，有效地筛选出可信的图像匹配结果，相比常规Kalman滤波算法，显著地提升了INS/SAR组合导航系统水平方向的定位精度。     

A Novel Speckle Filter for SAR Images Based on Informationtheoretic Heterogeneity Measurements

Most adaptive speckle filters are based on the local coefficient of variation, which serves to measure the heterogeneity of synthetic aperture radar (SAR) images. However, the sensitivity of the measurements to speckle and noise of SAR images would greatly deteriorate the speckle reduction. This article, based upon the information theory, presents a novel parameter for the heterogeneity measurement as a general index to quantitate the SAR image heterogeneity. Further, as a new speckle reduction algorithm based on the aforesaid quantitative heterogeneity measurements, it puts forward a heterogeneity-based speckle reduction filter (HBSRF), which uses the information-theoretic heterogeneity measurements as a criterion to classify the SAR images as belonging to homogeneous or heterogeneous regions. Then the finite iteration procedure and edge detection algorithms are adopted to strike the best balance between speckle reduction and edge preservation. The results from the computer simulation have demonstrated that the proposed effective method is superior to the conventional speckle filters based on the local coefficient of variation both in textural preservation and speckle reduction.     

保持弱细结构特征的SAR图象模拟退火重构方法

模拟退火 ( SA)算法最先由 White R G.用于合成孔径雷达 ( SAR)图象的降斑处理。该算法在重构均匀区域和强结构区效果有很大提高 ,但也有缺点 ,尤其是过分模糊弱细结构。本文提出了一种改进的方法 ,在 SA算法中融入了边沿检测和增强步骤 ,使弱细结构得以增强并在退火过程中保持。为配合此方法 ,采用平稳下降的指数温度规划取代对数形式。通过仔细调整算法过程 ,可使新方法保留 SAR图象中的很多细小结构 ,而不使其他均匀的和强结构场景性能恶化 ,同时也没有引入其他缺陷。改进的算法更加适于中、低分辨率的 SAR图象降斑处理     

A Generalized Approach to Multiresolution Complex SAR Signal Processing

Multiresolution synthetic aperture radar (SAR) image formation has been proven to be beneficial in a variety of applications such as improved imaging and target detection as well as speckle reduction. SAR signal processing traditionally carried out in the Fourier domain has inherent limitations in the context of image formation at hierarchical scales. We present a generalized approach to the formation of multiresolution SAR images using biorthogonal shift-invariant discrete wavelet transform (SIDWT) in both range and azimuth directions. Particularly in azimuth, the inherent subband decomposition property of wavelet packet transform is introduced to produce multiscale complex matched filtering without involving any approximations. This generalized approach also includes the formulation of multilook processing within the discrete wavelet transform (DWT) paradigm. The efficiency of the algorithm in parallel form of execution to generate hierarchical scale SAR images is shown. Analytical results and sample imagery of diffuse backscatter are presented to validate the method.     

Advanced high-order nonlinear chirp scaling algorithm for high-resolution wide-swath spaceborne SAR

Spaceborne Synthetic Aperture Radar (SAR) is a well-established and powerful imaging technology that can provide high-resolution images of the Earth’s surface on a global scale. For future SAR systems, one of the key capabilities is to acquire images with both high-resolution and wide-swath. In parallel to the evolution of SAR sensors, more precise range models, and effective imaging algorithms are required. Due to the significant azimuth-variance of the echo signal in High-Resolution Wide-Swath (HRWS) SAR, two challenges have been faced in conventional imaging algorithms. The first challenge is constructing a precise range model of the whole scene and the second one is to develop an effective imaging algorithm since existing ones fail to process high-resolution and wide azimuth swath SAR data effectively. In this paper, an Advanced High-order Nonlinear Chirp Scaling (A-HNLCS) algorithm for HRWS SAR is proposed. First, a novel Second-Order Equivalent Squint Range Model (SOESRM) is developed to describe the range history of the whole scene, by introducing a quadratic curve to fit the deviation of the azimuth FM rate. Second, a corresponding algorithm is derived, where the azimuth-variance of the echo signal is solved by azimuth equalizing processing and accurate focusing is achieved through a high-order nonlinear chirp scaling algorithm. As a result, the whole scene can be accurately focused through one single imaging processing. Simulations are provided to validate the proposed range model and imaging algorithm.     

Modified Frequency Scaling Algorithm for FMCW SAR Data Processing

This paper presents a modified frequency scaling algorithm for frequency modulated continuous wave synthetic aperture radar （FMCW SAR） data processing. The relative motion between radar and target in FMCW SAR during reception and between transmission and reception will introduce serious dilation in the received signal. The dilation can cause serious distortions in the reconstructed images using conventional signal processing methods. The received signal is derived and the received signal in range-Doppler domain is given. The relation between the phase resulting from antenna motion and the azimuth frequency is analyzed. The modified frequency scaling algorithm is proposed to process the received signal with serious dilation. The algorithm can effectively eliminate the impact of the dilation. The algorithm performances are shown by the simulation results.     

基于CZT的机载并行双站斜视SAR成像算法

建立了机载并行双站斜视合成孔径雷达(SAR)的几何模型,给出了雷达回波的数学表达式,推导了它的二维频谱并对其特点做了分析。在二维频域内,先用聚焦函数对观测场景中心的点目标做精确成像,然后用Chirp-Z变换(CZT)校正中心点两侧目标回波的距离徙动,再通过方位向逆傅里叶变换得到了雷达图像。该算法利用了CZT能够处理非线性调频信号的特点,简化了处理过程,提高了计算效率和成像精度。仿真实验验证了这种基于CZT的新算法在处理并行双站斜视SAR数据时的有效性。     

调频连续波SAR改进的频率尺度变换算法(英文)

本文提出了一种调频连续波SAR改进的频率尺度变换算法。调频连续波SAR在运动过程中持续不断地发射和接收信号,这种运动导致了回波信号的伸缩,对波前重建产生了严重的影响。推导了回波信号模型,给出了信号的距离-多普勒域表达式,分析了由于天线不断运动而导致的相位变化与方位向频率之间的关系。改进的频率尺度变换算法补偿了这种相位变化,实现了目标的精确成像,仿真结果表明了分析的正确性和算法的有效性。     

A non-local vectorial total variational model for multichannel SAR image speckle suppression

This paper aims at the multichannel synthetic aperture radar(SAR)image speckle reduction.This paper proposes a novel energy minimized regularization model for multichannel image denoising,which is an extension of the non-local total variational model for gray-scale image.It contains two terms,namely the vectorial data fidelity term and the non-local vectorial total variation term.The latter is constructed by high-dimensional non-local gradient that contains the structure information of the multichannel image.The existence and the uniqueness of the solution of the model are proved.A fixed point iterative algorithm is designed to acquire the solution of this model.The convergence property of this algorithm is proved as well.This model is applied to the multipolarimetric and multi-temporal RADARSAT-2 images despeckling.The result shows that this model performs better than the original vectorial total variational model on texture preserving.