多视SAR图像K分布特征函数与统计量研究

K分布是一种广泛应用于描述SAR图像杂波统计特性的概率模型,然而对于其特征函数及各类统计量的研究却少见于报道。本文基于Fourier变换和Mellin变换,详细推导了多视K分布第一类和第二类第一、第二特征函数的解析表达式,获得了原点矩、累积量、对数矩和对数累计量的计算公式,在此基础上给出了基于原点矩的参数估计器和基于对数累积量的参数估计器。最后利用Kendall近似展开法,理论分析了两种估计器的正规化偏差与方差。结果表明,对于小样本不均匀SAR图像场景,对数累积量估计器的性能明显优于矩估计器。      

基于Toeplitz矩阵特征值分解的SAR图像舰船目标检测方法

合成孔径雷达（SAR）图像舰船目标检测一直是海洋监测领域的重要手段。经典的恒虚警率（CFAR）检测依赖于分布模型及多参数的准确估计,难以适应复杂多变的海面背景。新兴的信息几何舰船检测方法挖掘了目标与杂波的统计差异,实现舰船的显著性表示,但依然受限于背景杂波的精确建模。考虑到现有方法的局限性,本文提出了一种基于Toeplitz矩阵特征值分解的SAR图像舰船目标检测算法。在无需寻求背景杂波分布模型的前提下,通过构建Toeplitz矩阵,以其特征值均值为检验统计量,充分获取目标与背景杂波的差异。在高分三号卫星和TerraSAR-X卫星实测SAR图像上的实验结果证明,相比于现有的多种典型方法,本文方法取得了更优的检测性能与更快的计算速度。      

SAR图像局部自适应ACCA-CFAR检测算法

该文在ACCA-CFAR(Automatic Censored Cell Averaging-CFAR)的基础上提出了一种以K分布对SAR图像杂波建模的局部自适应ACCA-CFAR目标检测算法。该算法首先估计局部窗口的K分布参数,然后根据参数确定局部ODV(Ordered Data Variability)门限,进而完成背景像素筛选,最后做出检测判决。文中证明了ODV门限与局部统计模型的参数有关,给出了采用局部自适应门限的理论依据。该文以海面舰船SAR图像为例,证明该算法在海面杂波背景中具有较少的虚警,可以完整地检测出舰船目标,保留更精细的结构特征。     

全卷积神经网络应用于SAR目标检测

在合成孔径雷达（SAR）图像目标检测中,由于场景杂波的复杂多变,对背景杂波统计模型估计难度增加,从而导致多数检测器容易受到背景杂波的干扰。针对如何避免场景杂波对目标检测干扰的问题,提出了一种基于全卷积神经网络的SAR目标检测模型。该模型将目标检测任务转化为像素分类问题,利用卷积神经网络对数据集中目标像素特征和背景杂波像素的先验信息进行自主学习,有效减少了虚警目标的数量;通过对目标及其阴影区域的联合检测,提高了目标的检测概率。对多个不同场景图像进行测试,实验结果表明提出的检测模型具有良好的检测性能和鲁棒性能,与传统恒虚警检测算法相比,在无需考虑背景杂波统计模型前提下有效降低了虚警概率。     

高分辨SAR图像中杂波的统计特性分析

为使SAR图像目标检测在复杂多变的地物杂波环境中获得最佳的性能,研究SAR图像中杂波的统计特性将是一件有意义的工作.在综合对比已有统计模型的基础上,从理论上重点分析了G0分布.运用实测SAR场景中表征不同地物类型的大量数据,从幅度直方图拟合、拟合精度检验等方面深入分析了杂波的统计特性.得出了在目前已有实用的统计模型中,C0分布最适合于描述SAR图像杂波统计特性,它是一种对于均匀、一般不均匀和极不均匀杂波区域建模的通用分布的新结论.因此,以C0分布为杂波模型的目标检测算法具有巨大的应用潜力.     

一种改进的高分辨率SAR图像超像素CFAR舰船检测算法

合成孔径雷达(SAR)图像舰船目标检测一直受到学者广泛关注,恒虚警率(CFAR)检测算法作为雷达图像经典目标检测算法被广泛应用于SAR图像舰船目标检测中。然而经典CFAR检测性能容易受到相干斑噪声影响,基于滑窗的检测结果对滑窗的尺寸选择非常敏感,难以保证杂波背景中不存在目标像素,并且计算效率较低。针对上述问题,该文提出了一种新的基于超像素无窗快速CFAR的SAR图像舰船目标检测算法。首先,利用基于密度的快速噪声空间聚类(DBSCAN)超像素生成方法生成SAR图像的超像素。在SAR数据服从混合瑞利分布的假设下,定义了超像素相异度。然后利用超像素精确估计每个像素的杂波参数,即使在多目标情况下,也可以克服传统CFAR滑动窗口的缺点。此外,基于SAR图像变异系数,提出了一种基于变异系数的局部超像素对比度来优化CFAR检测,以此消除大量杂波虚警,如陆地区域人造目标。对5幅SAR图像的实验结果表明,与其他方法相比,该文方法对不同场景SAR图像海面舰船目标检测都十分稳健。      

K分布海杂波参数估计方法研究

K分布模型在雷达杂波分析、建模、仿真及雷达目标检测中有着广泛应用,因此K分布杂波的参数估计方法非常重要。已有的K分布杂波的参数估计方法较多,然而在实际应用中缺乏从众多估计方法中选择合适方法的标准。本文针对常见的几类k分布参数估计方法,通过计算机仿真进行性能分析和比较,得出不同条件下选择参数估计方法的基本原则,并且将其应用于实际的海杂波数据建模分析中,从而对工程实践起到了指导作用。     

基于方差系数统计的合成孔径雷达相干斑强度估计

相干斑是合成孔径雷达(SAR)图像的固有属性。相干斑的强度是SAR图像解译的基础参量。由于多视处理假设模型等问题,相干斑的强度需要精确的估计。本文根据相干斑强度估计的基本原理,从统计学角度提出了一种基于方差系数统计分布的估计方法,该方法相比于传统方法可实现无监督自动估计相干斑的强度。本文所提出算法复杂度低,运算量小,具有很强的工程应用价值。     

基于Mellin变换的K分布参数估计新方法

 K分布是目前SAR图像建模领域应用最广泛、最著名的统计模型之一.当前普遍采用的是基于矩估计的参数估计方法,但其存在等效视数值需要经验获取、容易出现错误估计以及造成K分布失效等问题.为此,本文提出了一种基于Mellin变换的K分布参数估计新方法.该方法以Mellin变换为基础,详细推导了K分布对应的第一个、第二个第二类型的特征函数和它们各自对应的对数矩和对数累积量,最终获得了K分布参数估计简洁的迭代表达式.所提方法不但有效克服了K分布失效的问题,更为重要的是,其把视数同形状参数、尺度参数一样视为待估计的参数,且能够快速准确地迭代出它们的估计值,保证了K分布的拟合精度.实验结果证明了所提方法的有效性.     

基于图像分割的VHFSAR叶簇隐蔽目标差值变化检测

本文针对甚高频合成孔径雷达(VHF SAR)图像中树林区域后向散射呈现快速起伏的特点,提出了一种基于图像分割的叶簇隐蔽目标差值变化检测方法,该方法首先采用自动多阈值分割算法对参考图像进行分割以降低后向散射起伏对检测性能的影响,而后采用一种新的概率模型对分割后各图像区域的杂波分布分别进行准确估计以进一步提高算法的性能.实验结果表明本文方法较之其它算法具有更优的检测性能.     

Estimation of the Equivalent Number of Looks in Polarimetric Synthetic Aperture Radar Imagery

This paper addresses estimation of the equivalent number of looks (ENL), an important parameter in statistical modeling of multilook synthetic aperture radar (SAR) images. Two new ENL estimators are discovered by looking at certain moments of the multilook polarimetric covariance matrix, which is commonly used to represent multilook polarimetric SAR (PolSAR) data, and assuming that the covariance matrix is complex Wishart distributed. First, a second-order trace moment provides a polarimetric extension of the ENL definition and also a matrix-variate version of the conventional ENL estimator. The second estimator is obtained from the log-determinant matrix moment and is also shown to be the maximum likelihood estimator under the Wishart model. It proves to have much lower variance than any other known ENL estimator, whether applied to single-polarization or PolSAR data. Moreover, this estimator is less affected by texture and thus provides more accurate results than other estimators should the assumption of Gaussian statistics for the complex scattering coefficients be violated. These are the first known estimators to use the full covariance matrix as input, rather than individual intensity channels, and therefore to utilize all the statistical information available. We finally demonstrate how an ENL estimate can be computed automatically from the empirical density of small sample estimates calculated over a whole scene. We show that this method is more robust than procedures where the estimate is calculated in a manually selected region of interest.     

Reflectivity estimation for multibaseline interferometric radar imaging of layover extended sources

In recent years, there has been great interest in exploiting the advanced multibaseline operation of synthetic aperture radar interferometry (InSAR) for solving layover effects from complex orography, which can degrade both SAR and InSAR imagery of terrain radar reflectivity and height. In this work, the problem of retrieving radar reflectivity of layover areas is addressed. It is formulated as the problem of estimating a multicomponent sinusoidal signal corrupted by multiplicative complex correlated noise and additive white Gaussian noise. Application of nonparametric [e.g., Capon, amplitude and phase estimation filter (APES)], parametric [least squares, modern parametric RELAXation spectral estimator (RELAX)], and hybrid spectral estimators for amplitude estimation is investigated for a multilook scenario. In particular, the multilook extensions of RELAX and APES are applied to the interferometric problem. Performance analysis is investigated through a Cramer-Rao lower bound calculation and Monte Carlo simulation. The method of least squares, coupled with Capon's approach to spatial frequency estimation, multilook APES, and multilook RELAX turn out to provide accurate reflectivity estimates for undistorted multibaseline image formation of layover areas.     

Statistics of the Stokes parameters and of the complex coherenceparameters in one-look and multilook speckle fields

Barakat [1987] derived the Stokes parameter statistics, applicable to one-look synthetic aperture radar (SAR) images, of a partially polarized wave backscattered from a Gaussian area. In this paper, the statistics of the Stokes parameters and of the phase difference are derived as a function of the mean effective phase difference and the degree of coherence for one-look and multilook SAR data. The statistics of the degree of coherence are also derived for multilook SAR data. It is shown that the estimator currently used for calculation of the degree of coherence is biased under low coherence conditions     

On the Extension of Multidimensional Speckle Noise Model From Single-Look to Multilook SAR Imagery

Speckle noise represents one of the major problems when synthetic aperture radar (SAR) data are considered. Despite the fact that speckle is caused by the scattering process itself, it must be considered as a noise source due to the complexity of the scattering process. The presence of speckle makes data interpretation difficult, but it also affects the quantitative retrieval of physical parameters. In the case of one-dimensional SAR systems, speckle is completely determined by a multiplicative noise component. Nevertheless, for multidimensional SAR systems, speckle results from the combination of multiplicative and additive noise components. This model has been first developed for single-look data. The objective of this paper is to extend the single-look data model to define a multilook multidimensional speckle noise model. The asymptotic analysis of this extension, for a large number of averaged samples, is also considered to assess the model properties. Details and validation of the multilook multidimensional speckle noise model are provided both theoretically and by means of experimental SAR data acquired by the experimental synthetic aperture radar system, operated by the German Aerospace Center     

On the multilook images of moving targets by synthetic aperture radars

In the multilook processing of synthetic aperture radar (SAR) data, subapertures are synthesized at different center times so that a time-lapse exists between looks. This does not affect the imaging of stationary targets but if targets are in motion, the information content about the targets differs from look to look. The purpose of this paper is to investigate the effects of motions on the SAR multilook images of moving targets. Expressions are derived for the impulse response function from a moving point target in terms of the look number and the nature of the motion. Discussions are given only on the effects inherent to multilook processing.     

An Adaptive and Fast CFAR Algorithm Based on Automatic Censoring for Target Detection in High-Resolution SAR Images

An adaptive and fast constant false alarm rate (CFAR) algorithm based on automatic censoring (AC) is proposed for target detection in high-resolution synthetic aperture radar (SAR) images. First, an adaptive global threshold is selected to obtain an index matrix which labels whether each pixel of the image is a potential target pixel or not. Second, by using the index matrix, the clutter environment can be determined adaptively to prescreen the clutter pixels in the sliding window used for detecting. The $G^{0}$ distribution, which can model multilook SAR images within an extensive range of degree of homogeneity, is adopted as the statistical model of clutter in this paper. With the introduction of AC, the proposed algorithm gains good CFAR detection performance for homogeneous regions, clutter edge, and multitarget situations. Meanwhile, the corresponding fast algorithm greatly reduces the computational load. Finally, target clustering is implemented to obtain more accurate target regions. According to the theoretical performance analysis and the experiment results of typical real SAR images, the proposed algorithm is shown to be of good performance and strong practicability.      

Improved multilook techniques applied to SAR and SCANSAR imagery

The multilook processing used in SAR (synthetic aperture radar) image formation to reduce the speckle noise is considered. Two multilook techniques are proposed for improving the radiometric resolution without altering the geometric resolution and the characteristics of the impulse response. These techniques are based on the formation of looks with different bandwidths. The final image is formed by giving each look a proper size and weighting, and by adding them incoherently. The looks with wide bandwidth contribute to an improvement of the overall geometric resolution, while the looks with narrow bandwidth improve the overall radiometric resolution. The equivalent number of looks is more than 2.3 times the number of independent looks and is superior to conventional multilook processing with overlapping. Finally, using the proposed techniques, an algorithm for efficient SAR and ScanSAR processing is presented, and its validity is proved by image comparison and analysis     

Signal subspace change detection in averaged multilook SAR imagery

This paper addresses change detection in averaged multilook synthetic aperture radar (SAR) imagery. Averaged multilook SAR images are preferable to full-aperture SAR reconstructions when the imaging algorithm is approximation-based (e.g., polar format processing) or when motion data are not accurate over a long full aperture. We examine the application of a SAR change-detection method, known as signal subspace processing, which is based on the principles of two-dimensional adaptive filtering, and we use it to recognize the addition of surface landmines to a particular area under surveillance. We describe the change-detection problem as a trinary hypothesis testing problem, and define a change signal and its normalized version to determine whether: 1) there is no change in the imaged scene; 2) a target has entered the imaged scene; or 3) a target has exited the imaged scene. A statistical analysis of the error signal is provided to show its properties and merits. Results are presented for averaged noncoherent multilook and coherent single-look X-band SAR imagery.