基于角点特征的SAR图像与光学图像匹配算法

INS／SAR组合导航系统对SAR实时图像与光学参考图像的匹配算法提出了实时性和准确性要求。文章首先采用一种结合Harries算子与曲率尺度空间的算法,提取SAR图像与光学图像中的角点;然后利用距离约束、角点值约束、边缘约束进行角点匹配。经实验验证,该方法实时性好,匹配精度高,可较好的应用于INS／SAR组合导航系统的...     

Matching suitable feature construction for SAR images based on evolutionary synthesis strategy

In the paper,a set of algorithms to construct synthetic aperture radar（SAR）matching suitable features are frstly proposed based on the evolutionary synthesis strategy.During the process,on the one hand,the indexes of primary matching suitable features（PMSFs）are designed based on the characteristics of image texture,SAR imaging and SAR matching algorithm,which is a process involving expertise;on the other hand,by designing a synthesized operation expression tree based on PMSFs,a much more flexible expression form of synthesized features is built,which greatly expands the construction space.Then,the genetic algorithm-based optimized searching process is employed to search the synthesized matching suitable feature（SMSF）with the highest effciency,largely improving the optimized searching effciency.In addition,the experimental results of the airborne synthetic aperture radar ortho-images of C-band and P-band show that the SMSFs gained via the algorithms can reflect the matching suitability of SAR images accurately and the matching probabilities of selected matching suitable areas of ortho-images could reach 99±0.5%.     

基于复Shearlet域高斯混合模型的SAR图像去噪

 结合双树复小波的平移不变性、多分辨率性和剪切波变换的灵活可选的多方向性,提出一种新的图像表达方法——复Shearlet变换。针对合成孔径雷达(Synthetic Aperture Radar,SAR)图像的相干噪声特点,建立了复Shearlet系数域的高斯混合模型(Gaussian Mixture Model,GSM),在此基础上应用贝叶斯最小二乘法进行系数估计,最后进行复Shearlet反变换得到去噪以后的SAR图像。仿真结果和分析表明:本文提出的算法相比其他变换域去噪算法,不仅去噪后的图像的峰值信噪比(Peak Signal to Noise Ratio, PSNR)有所提高,而且去噪后的图像更平滑,且与Shearlet域高斯混合模型相比,本文算法速度快了两倍多。     

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。     

末制导DBS图像匹配方法研究

提出了一种适于工程应用的末制导DBS图像匹配方法,采用DBS成像,结合目标场景中强散射点的空间位置关系实现基于模板的目标场景匹配,快速定位及打击目标,较好地解决了末制导成像识别及定位问题。实测数据仿真结果表明,基于模板的DBS图像匹配算法可抑制多种图像畸变,具有较高的匹配可靠性和匹配精度,满足了雷达导引头DBS图像识别的工程使用要求,具有较强的实用价值。     

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.     

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.     

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     

合成孔径雷达系统建模、仿真与信号处理初探

作为雷达技术发展历史中的里程碑,合成孔径雷达(SAR)通过使用空中合成天线阵列技术及先进的目标回波信号处理技术能够提供清晰的地球表面图像。由于它的这一突出特点,SAR已经成为许多飞行器的重要任务载荷并被广泛应用于军事及民用领域。从航空电子系统总体需求角度出发,为了深刻理解SAR系统的工作原理并得到更好的SAR图像产品,有必要对系统数学模型的建立、SAR回波信号的仿真以及信号处理算法进行深入的研究。本文试图从这三方面讨论SAR系统设计中的关键问题。     

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.     

SAR图像匹配制导精度影响因素分析

合成孔径雷达（SAR）具有高分辨率、全天候等优点,是提高精确制导武器制导精度的有力工具。制导精度是精确制导武器的重要性能指标,影响SAR制导系统精度的主要因素有实时图的获取误差及预处理误差、图像匹配误差、惯导测量误差、SAR制导特殊弹道引起的导航制导的误差。概述了SAR图像匹配制导系统精度的相关研究,对比和分析了这些研究和结论,指出了该研究存在的问题和发展方向。     

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。     

Phase quantized SAR signal processing: theory and experiments

A complete theory of synthetic aperture radar (SAR) processing from phase-only data is presented, for both analogue and coded raw signals and reference functions. Appropriate processing architectures are presented as well as quality indexes to judge performance of the selected coding. The analysis encompasses both images and interferometric fringes for interferometry SAR (IFSAR) application. Theoretical results are validated by a large number of experiments, comparing the performance of the suggested coding levels, and their combinations between raw and reference functions. Experiments are extended until the comparison of final digital elevation models     

OGSRN: Optical-guided super-resolution network for SAR image

Although Convolutional Neural Networks(CNNs) have significantly improved the development of image Super-Resolution(SR) technology in recent years, the existing SR methods for SAR image with large scale factors have rarely been studied due to technical difficulty. A more efficient method is to obtain comprehensive information to guide the SAR image reconstruction.Indeed, the co-registered High-Resolution(HR) optical image has been successfully applied to enhance the quality of SAR image due to it...     

Bayesian edge detector for SAR imagery using discontinuity-adaptive Markov random feld modeling

Synthetic aperture radar（SAR）image is severely affected by multiplicative speckle noise,which greatly complicates the edge detection.In this paper,by incorporating the discontinuityadaptive Markov random feld（DAMRF）and maximum a posteriori（MAP）estimation criterion into edge detection,a Bayesian edge detector for SAR imagery is accordingly developed.In the proposed detector,the DAMRF is used as the a priori distribution of the local mean reflectivity,and a maximum a posteriori estimation of it is thus obtained by maximizing the posteriori energy using gradient-descent method.Four normalized ratios constructed in different directions are computed,based on which two edge strength maps（ESMs）are formed.The fnal edge detection result is achieved by fusing the results of two thresholded ESMs.The experimental results with synthetic and real SAR images show that the proposed detector could effciently detect edges in SAR images,and achieve better performance than two popular detectors in terms of Pratt＇s fgure of merit and visual evaluation in most cases.     

星载合成孔径雷达数学模型的研究

根据合成孔径雷达的基本原理，利用傅立叶变换的性质，详尽地给出了星载合成孔径雷达回波信号的数学模型的推导过程，以及相应的距离变化函数的展开过程，为模拟合成孔径雷达回波信号和对回波信号处理提供了数学依据。     

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.     

惯性信息辅助的大视角目标快速精确定位

目标定位技术广泛应用于航空领域的侦察机、无人机等各类侦察打击任务中,目标定位精度的高低及效率对作战效果具有重要影响。针对仿射尺度不变的特征变换(ASIFT)算法对远距离大视角目标定位精度较低、速度较慢的问题,提出了一种基于惯性信息辅助的大视角目标快速精确定位方法。该方法首先对目标实测序列图像构造尺度空间,结合FAST特征检测与FREAK特征描述的方式进行匹配,实现对待定位目标的快速提取;然后利用机载惯性信息求解目标实测图与参考图之间的透视变换矩阵,利用该矩阵对实测图进行变换以减小图像间视角差异,克服了ASIFT算法盲目匹配计算的弊端,并通过FAST特征检测与FREAK特征描述相结合的方式提升了大视角图像的匹配速度;最后通过单应性矩阵映射关系实现对目标的精确定位。实验结果表明,大视角目标快速精确定位方法匹配耗时比ASIFT算法的减小了1个数量级,定位精度比目标平均值定位算法精度提高了1个数量级,有效提高了图像匹配定位在航空领域的应用效率。     

基于Gibbs-Markov随机场与连通聚类的SAR图像恢复

在传统的马尔可夫随机场(MRF)的图像建模方法基础上利用合成孔径雷达(SAR)图像的固有特性对Gibbs-MRF模型进行改进复原SAR图像,并进一步提出用数字形态学中连通性理论进行图像分割。在SAR图像像素空间的邻域内,估计最大后验概率(MAP)时引用Gamma分布代替传统的瑞利分布恢复数据,同时利用像素强度值相关性的连通模型将目标较好地提取出来。充分利用了SAR图像的数字形态信息和像素强度之间的相关性,得到了更好的分割效果。仿真实验说明本文方法是有效的。     

基于先验误差模型的机载高分宽幅DBF-SAR自聚焦算法

高分宽幅（HRWS）数字波束形成（DBF）合成孔径雷达（SAR）利用多通道空间采样代替部分时域采样,可以有效缓解SAR成像时高分辨率与宽测绘带间的矛盾,具有重要的军用和民用价值。现有常规DBF-SAR成像算法都假设雷达传感器相对位置精确已知,实际应用中受传感器位置测量误差影响,由位置不精确导致的相位误差会严重影响DBF-SAR高精度成像能力。在极坐标格式算法（PFA）框架下,推导了DBF-SAR成像处理后,残留相位误差的解析模型,分析了该误差对成像质量的影响。依据推导的先验相位误差解析结构模型,提出了一种基于图像对比度最优化准则的自聚焦算法。新算法通过引入先验相位结构信息,极大降低了待估参数的空间维数,可以同时改善自聚焦算法的参数估计精度和计算效率。数据处理结果验证了理论分析的正确性和所提算法的有效性。