采用螺旋散射的SAR极化定标参考地物提取方法

极化合成孔径雷达观测系统获取的影像需要经过极化定标处理才能进行定量的分析与应用。当前的极化定标方案普遍采用分布式地物解算串扰和交叉极化通道不平衡误差,需要在定标前选取满足一定散射特征的分布式地物作为定标参考样本。利用螺旋散射的极化特征与分布特点,提出了一种新的极化定标参考地物自动提取方法。该方法根据极化目标分解构建螺旋散射比率特征,并采用自适应阈值分割方法自动提取地物样本。采用C波段机载极化雷达影像进行实验,结果表明,所提方法能够保持影像极化定标的准确性,并能提高极化定标的精度。     

简缩极化特征值分析的溢油检测

为有效利用简缩极化SAR进行海洋溢油检测,本文基于简缩极化特征值分析,提出了3个用于简缩极化溢油检测的参数,引入了基于简缩极化特征值分解的简缩极化熵Hc(Compact Polarization Entropy)、简缩极化比参数PFc(Compact Polarization Fraction)、简缩极化基准高度PHc(Compact Polarization Pedestal Height)特征进行海洋溢油检测。海表的散射类型主要为低熵散射(小粗糙面发生的Bragg散射),为弱去极化、弱散射过程随机性状态,由于溢油会阻尼海水的Bragg散射,使其熵值变高、呈去极化、强散射过程随机性状态,故简缩极化熵、简缩极化比参数和简缩极化基准高度可以用来检测海洋溢油。本文采用C波段的Radarsat-2、SIR-C/X-SAR数据进行了实验,结果表明:简缩极化熵、简缩极化比参数和简缩极化基准高度能够有效抑制疑似溢油,使海水与疑似溢油差异变小;突出溢油区域,使海水与溢油的可区分性变大。     

LSSVM算法在极化SAR影像分类中的应用

最小二乘支持向量机(LSSVM)是针对标准支持向量机(SVM)算法训练时间长的问题而提出的一种改进算法。针对SVM算法在极化SAR影像分类时存在效率较低的问题,以目标分解理论为基础,对LSSVM算法应用于极化SAR影像分类的有效性进行了研究。结果表明,对于极化SAR影像分类,LSSVM算法与SVM算法的分类精度相当,但时间效率远优于SVM算法,并且对参数的调整也具有更好的稳定性,同时泛化能力良好。     

Data Compression for Multilook Polarimetric SAR Data

This letter attempts to address the problem on the emergence of negative eigenvalues in the coherency matrix after the compressing of multilook polarimetric synthetic aperture radar (SAR) data. A new nine-parameter expression for the eigenvalue decomposition of the coherency matrix is introduced, and a new compression algorithm is proposed for multilook polarimetric data with this expression. By comparing it with the NASA/Jet Propulsion Laboratory's Airborne SAR compression algorithm, the authors analyze the new algorithm's compression accuracy, signal-to-noise ratio, and the ability to preserve the data's polarimetric property. For polarimetric SAR data, it is important to preserve the polarimetric property of a target. The proposed algorithm has this ability which is illustrated by the comparison of the polarimetric signatures. Finally, the effectiveness of the proposed methods is demonstrated by using the experimental SAR data.      

Polarimetric synthetic aperture radar change detection for specific land cover types

This paper presents a supervised polarimetric synthetic aperture radar (PolSAR) change detection method applied to specific land cover types. For each pixel of a PolSAR image, its target scattering vector can be modeled as having a complex multivariate normal distribution. Based on this assumption, the joint distribution of two corresponding vectors in a pair of PolSAR images is derived. Then, a generalized likelihood ratio test statistic for the equality of two likelihood functions of such joint distribution is considered and a maximum likelihood distance measure for specific land cover types is presented. Subsequently, the Kittler and Illingworth minimum error threshold segmentation method is applied to extract the specific changed areas. Experiments on two repeat-pass Radarsat-2 fully polarimetric images of Suzhou, China, demonstrate that the proposed change detection method gives a good performance in determining the specific changed areas in PolSAR images, especially the areas that have changed to water.     

利用SVM的全极化、双极化与单极化SAR图像分类性能的比较

支持向量机(SVM)以其在小训练样本时良好的分类性能,目前已广泛应用于多个领域.本文在极化SAR图像特征提取基础上,将SVM应用于极化SAR图像分类,定性和定量地比较了全极化、双极化和单极化SAR图像的分类性能,分析了不同的极化组合对分类结果的影响,并根据地物极化散射特性分析了分类精度差异的成因.实测极化SAR数据的实验结果表明,全极化数据能获得最好的分类性能,双极化次之,单极化最低,且在某些情况下,双极化与全极化分类性能接近.     

基于多分辨率特征的UWB SAR二维广义似然比目标检测方法

针对超宽带合成孔径雷达(UWB SAR)工作体制及探测背景的特殊性,结合成像过程,分析了不同分辨率条件下目标与杂波的区别,在此基础上采用了两种形式的一阶自回归(AR)模型实现对多分辨率序列的建模,并提出了广义似然比(GLR)的二维计算方法.该方法大大提高了多分辨率特征提取的稳定性,基于实际UWB SAR图像的试验结果表明:利用多分辨率特征可明显增强图像信杂比,从而提高UWB SAR目标检测效果.     

Ground Moving Target Indication Using an InSAR System With a Hybrid Baseline

In this letter, a two-channel airborne experimental interferometric synthetic aperture radar (InSAR) designed for terrain height estimation is exploited to acquire the ability of ground moving target indication (GMTI). Due to the hybrid baseline of this system, the interferometric phase changes with the target motion as well as the terrain height. The fluctuation of the interferometric phase worsens the performance of the clutter suppression and the radial velocity estimation. In order to resolve this problem, a GMTI method with three steps is proposed. After two steps are used to eliminate the local flat-Earth phase and the cross-track interferometric phase of the scene, respectively, an adaptive filtering method is used to suppress the stationary clutter with the benefit of calibrating the sensor responses. A conventional constant false alarm rate detector is then used to indicate the moving targets. The validity of the proposed method is demonstrated with real data collected using an experimental airborne InSAR system.      

一种求解分布式目标通道最优极化的快速算法

针对现有分布式目标通道最优极化算法存在运算量偏大等问题,以算法的实用性为目的,在理论分析的基础上提出一种求解分布式目标通道最优极化的快速算法.首先将任意通道下的天线接收功率模型统一为同极化通道下的天线接收功率拓展模型,然后对该拓展模型进行变换极化基处理,在此基础上理论确定目标最优极化在(r,θ)平面上的位置区间,从而为简化目标最优极化求解或预判目标最优极化位置等提供理论支撑.为获取目标最优极化,采用区间二分法在目标最优极化位置区间内迭代搜索.通过对比实验对算法运算速度和实现方面予以验证.

Abstract：

Aiming at the large mount of calculation of the traditional algorithms for polarimetric power optimization of random target in arbitrary channel, a fast algorithm is proposed in this article. Firstly, the function of received power in arbitrary channel is unified as the form of copolar power. Then based on the change of polarimetric basis,the copotar power is analyzed theoretically to obtain the minimum interval of target optimal polarization state in (r,θ)plane, which provides theoretic support for simplifying the process of obtaining optimal polarization states or anticipating their positions. In order to obtain optimal polarization states, the interval dichotomy is used to search in the minimum interval of target optimal polarization state, The experiment results have demonstrated that the proposed algorithm has better performance than the Lagrange multiplier method or the method of traversal search in algorithmic realization and computational speed.     

一种扩展的基于结构检测的最优多视极化SAR相干斑滤波算法

全极化数据的可得,使得利用极化散射矩阵以减少多视全极化SAR图像中的相干斑成为了可能。其中,被称为最优的多视极化白化滤波器（MPWF）就是一个典型例子。然而,为提高滤波器参数估计的精度,同时能够自适应的检测图像中的结构特征,在滤波时采用适当的窗算法是必要的。本文提出了两个有效的窗算法,并用1994年NASA SIR-C/X-SAR,L band,经过四视处理的天山森林的极化数据进行了仿真。实验结果表明,这两种算法不仅很好的达到了降噪效果,而且对图像的纹理信息以及结构特征（即边缘特征、线性特征、强散射体特征）的保持效果是最佳的。     

利用矩阵值域的极化干涉SAR相干性的研究

极化SAR干涉测量 (PolInSAR)的相干性是反演植被参数的重要信息来源,极化空间中不同极化状态对应的相干性分布与复极化相干矩阵的值域相关。本文讨论了不同结构的复极化相干矩阵值域的特点,分析了不同极化状态下干涉相干性与复极化相干矩阵的值域的关系。利用模拟数据和真实全极化SAR数据分析了滑动窗口大小和不同散射体对复极化干涉矩阵值域的影响,以及复极化干涉矩阵的结构对极化干涉SAR相干性分布空间的影响,有助于更加准确地获取极化干涉SAR最优极化基和估计最优相干性。     

面向多基线干涉SAR高程反演的全局最优相干方法

本文针对多基线极化干涉SAR数据,提出了面向多基线干涉SAR高程反演的全局最优相干方法。该方法将多景全极化干涉影像联合在一起,构建多基线极化相干矩阵,由多基线最优相干准则指导,求解全局条件下的最优干涉图。该方法可以有效降低多基线干涉中散射中心不一致对干涉相位影响,从而提高干涉相位的精度和可靠性,并提高最终获取DEM的精度。利用国产X-SAR系统和德国E-SAR系统获取的多基线全极化数据进行全局最优相干方法试验,利用多基线极化最优相干方法生成全局条件下的最优干涉图,依据多基线高程反演方法计算目标高程,验证了本文提出的方法的有效性。     

A study on the polarimetric properties of various features using SIR-C data

Spaceborne Imaging Radar (SIR-C) data acquired over Gujarat, India in 1994 were processed and analysed using differnet techniques applicable to polarimetric SAR data such as polarization signatures, polarization index, decomposition of the signal and polarization phase difference and limited groundtruth data. It has been observed that multi-frequency polarimetric data enhances the potential of retrieving geo-physical parameters. The polarization signatures are found to vary with the nature of the target. Target decomposition of the returned signal will be useful for the classification of various features. Polarization Phase Difference (PPD) gives good information about the vegetation parameters.     

Polarimetric Dual-Baseline InSAR Building Height Estimation at L-Band

This letter generalizes a multibaseline interferometric synthetic aperture radar (InSAR) signal model to the polarimetric scenario. Based on this formulation, two high-performance spectral analysis techniques are adapted to process multibaseline Pol-InSAR observations. These new methods enhance the height estimation of scatterers by calculating optimal polarization combinations and allow the determination of their physical characteristics. Applying the proposed algorithms to urban environments, the building layover problem is analyzed by means of polarimetric dual-baseline InSAR measurements: the ground and building height are estimated. The techniques are validated using dual-baseline Pol-InSAR data acquired by DLR's Experimental SAR (E-SAR) system over Dresden city.      

极化SAR参数优化与光学波谱相结合的面向对象土地覆盖分类

提出一种基于极化参数优化的面向对象分类方法。该方法结合光学和SAR数据,有效提高了对地物的识别能力。本文方法的关键在于:在■分解中,使用光学影像指导SAR影像选择同质点,使其更精确地估计极化参数并结合光学波谱信息作为输入特征;使用面向对象的分类方法,仅将光学影像作为分割输入,避免SAR噪声引起的分割错误。以美国Bakersfield地区的Sentinel-1/2数据为例,确定7种地物类型,对比分析不同输入与不同分类器对分类结果的影响。研究表明,优化输入参数在纹理丰富区域能够有效提高分类精度;面向对象的分类结果更加稳定并较好地维持地表几何特征;改进分类方法较传统分类方法总体精度提高了近10%,达到92.6%。     

3维块匹配小波变换的极化SAR非局部均值滤波

极化合成孔径雷达(SAR)图像受相干斑噪声的影响,难以很好地保持结构特性,针对这个问题提出了一种采用3维块匹配小波变换的非局部均值滤波算法NL-3DWT(Nonlocal Filter based on 3-D Patch Matching Wavelet Transform)。该算法使用块匹配的3维非抽样小波变换对极化总功率图进行预滤波,在此基础上使用边界对齐窗提取结构相似像素,同时使用Sigma范围选择极化SAR数据的散射相似像素,共同构成相似像素集合;构建结构保持权重函数增大图像结构信息在块相似性度量时的权重,最终实现极化SAR图像结构保持的相干斑抑制。该算法增强了图像结构特征的表达,提高了结构相似像素选择的准确性,机载极化SAR数据实验结果表明,NL-3DWT算法能够在抑制相干斑噪声的同时,更有效地保持极化SAR图像的结构特性和极化散射特性。     

Polarimetric differential SAR interferometry in an arid natural environment

Ground deformation measurements have contributed to a better understanding of the processes and mechanisms involved in natural hazards. Those include landslides, subsidence, earthquakes and volcanic eruptions. Spaceborne Differential Interferometric Synthetic Aperture RADAR (DInSAR) is a well studied technique for measuring ground deformation. Quality of deformation measurements, however, is often degraded by decorrelation. With the advent of fully polarimetric SAR satellite sensors, polarimetric optimization techniques exploiting polarimetric diversity improve the phase quality of interferograms. In this paper, we analyzed three polarimetric optimization methods to determine the optimal one for application in an arid natural environment. We considered coherence decomposition in single and double phase center scenarios. Coherence estimation bias associated with each optimization method has been analyzed. We compared the derived displacement values with terrestrial GPS measurements. The study shows that polarimetric optimization increases the number of coherent pixels by upto 6.89% as compared with a single polarization channel. The study concludes that polarimetric optimization coupled with DInSAR analysis yields more reliable deformation results in a low coherence region.     

Using the Existing Spectral Clutter Filter With the Nonuniformly Spaced Time Series Data in Weather Radar

The National Weather Service (NWS) has a network of weather surveillance Doppler radars, WSR-88D, that is routinely upgraded to reflect current technological and engineering advances. During the last decade, the staggered pulse repetition time (SPRT) was proposed to mitigate range/velocity ambiguity in WSR-88D; however, it could not be used at lowest elevation tilts due to the inability to filter ground clutter from the nonuniformly spaced time series. A complicated spectral procedure was developed to address this issue, but the procedure was derived for a specific set of data acquisition parameters and used a lookup table to provide a value for the clutter spectrum width. Attempts to use SPRT with different sets of acquisition parameters always led to the degradation of filtering. It is proposed here that the clutter spectrum width be estimated by using Gaussian model adaptive processing (GMAP) that is currently used by NWS for uniformly sampled time series. GMAP is an adaptive ground clutter filter that performs an iterative fit of a Gaussian curve to the spectral coefficients identified as being due to ground clutter. GMAP cannot be used directly with the SPRT spectrum because of multiple clutter replicas that are due to staggered nonuniform sampling. However, the elements of GMAP can be exploited and used in the SPRT procedure. This letter presents how the elements of GMAP can be used with the SPRT data to provide successful clutter filtering at lowest elevation tilts.      

2L-IHP目标检测算法及其在AIRSAR数据中的应用

简要介绍了2L—IHP（Two-Looks Internal Hermitian Product）算法，并针对实际情况对其作了相应的调整和改进。主要是突破算法对数据源的限制，使得它可以应用到幅度图像中。对于极化SAR图像，使用PWF（Polarimetric Whitening Filter）方云将3个通道的图像合成为一幅检测图，再进行目标检测。利用ADTS（Advanced Detection Technology Sensor）数据，对以上各种算法的检测效果进行了分析比较。应用C、L、P波段的AIRSAR极化数据进行试验，发现3个波段中，L和C波段的检测效果最好；4种极化方式中，HH极化取得最佳的检测效果；并且得出全极化数据的检测结果优于单极化数据的结论。但以上结论还有待进一步验证。     

A Tool Assessing Optimal Multi-Scale Image Segmentation

Image segmentation to create representative objects by region growing image segmentation techniques such as multi resolution segmentation (MRS) is mostly done through interactive selection of scale parameters and is still a subject of great research interest in object-based image analysis. In this study, we developed an optimum scale parameter selector (OSPS) tool for objective determination of multiple optimal scales in an image by MRS using eCognition software. The ready to use OSPS tool consists of three modules and determines optimum scales in an image by combining intrasegment variance and intersegment spatial autocorrelation. The tool was tested using WorldView-2 and Resourcesat-2 LISS-IV Mx images having different spectral and spatial resolutions in two areas to find optimal objects for ground features such as water bodies, trees, buildings, road, agricultural fields and landslides. Quality of the objects created for these features using scale parameters obtained from the OSPS tool was evaluated quantitatively using segmentation goodness metrics. Results show that OSPS tool is able determine optimum scale parameters for creation of representative objects from high resolution satellite images by MRS method.