基于酉ESPRIT算法的极化干涉相位估计

目前SAR极化干涉测量地形参数已经成为一种新兴的前沿技术。在现有提取极化干涉相位的技术中,由空间谱估计理论发展而来的,利用MUSIC、TLS-ESPRIT算法获取干涉相位信息的方法正逐步完善起来。但由于SAR信号存在散射点的观测数据少的问题,利用上述方法往往不能得到更高精度的干涉相位。作者提出的基于酉ESPRIT算法估算干涉相位的方法,充分利用了复观测数据以及共轭数据中的信息,使得观测数据等效增加了一倍,从而提高了植被高度参数的估计精度。本文详细阐述了该方法的原理和实施步骤,并通过对SIR-C/X-SAR的L波段实际数据进行验证处理,表明酉ESPRIT算法十分有效。     

极化干涉SAR森林高度反演方法研究

在分析随机体散射体/地表二层(RVoG)散射模型的基础上,利用德国宇航局机载SAR系统(ESAR)获取的POLInSAR数据和森林高度地面观测数据,对多种已有的森林高度反演模型进行了比较评价,从物理机制上对试验结果进行了分析、解释,进而发展了一种基于极化相干优化和非体散射去相干补偿的综合反演方法,实验结果表明,基于该方法的树高反演效果总体上优于其他方法。     

Adaptive filter in SAR interferometry derived DEM

IntroductionRadar interferometry (InSAR) has been suc-cessfully applied to measure the surface topogra-phyin the past two decades[1-4].Since InSARisa coherent technology ,the most i mportant con-straint for the radar echo is coherence . Howev-er ,decorrelation is al ways inevitably introducedby the thermal noise , geometric decorrelation,Doppler centroid decorrelation, volume scatter-ing decorrelation,temporal decorrelation, orbiterror , at mospheric delay , and data processingnoise[5-6]. …     

自交叉双边滤波的极化SAR数据相干斑抑制

相干斑抑制是极化SAR数据预处理的关键步骤。双边滤波是一种空域和值域滤波相结合的优秀边缘保持滤波算法。针对双边滤波在抑制极化SAR数据相干斑的不足,该文将改进的交叉双边滤波引入到极化SAR数据降噪领域,加入散射机制测度来扩展原权重核,根据SPAN图像的局域变差系数自动调整空间方差系数,利用参考图像来度量灰度值和散射机制相似性。实验结果表明:本文方法较经典滤波算法有更强的噪声平滑能力和更好的细节信息保持能力,在保持原数据极化散射信息方面也表现出良好的性能,这为基于极化SAR数据的后续应用提供了支持。     

SAR polarimetric change detection for flooded vegetation

Abstract

Due to spatial and temporal variability an effective monitoring system for water resources must consider the use of remote sensing to provide information. Synthetic Aperture Radar (SAR) is useful due to timely data acquisition and sensitivity to surface water and flooded vegetation. The ability to map flooded vegetation is attributed to the double bounce scattering mechanism, often dominant for this target. Dong Ting Lake in China is an ideal site for evaluating SAR data for this application due to annual flooding caused by mountain snow melt causing extensive changes in flooded vegetation. A curvelet-based approach for change detection in SAR imagery works well as it highlights the change and suppresses the speckle noise. This paper addresses the extension of this change detection technique to polarimetric SAR data for monitoring surface water and flooded vegetation. RADARSAT-2 images of Dong Ting Lake demonstrate this curvelet-based change detection technique applied to wetlands although it is applicable to other land covers and for post disaster impact assessment. These tools are important to Digital Earth for map updating and revision.     

Crop characterization using an improved scattering power decomposition technique for compact polarimetric SAR data

Crop characterization using Compact-Pol Synthetic Aperture Radar (CP-SAR) data is of prime interest with the rapid advancements of SAR systems towards operational applications. It is noteworthy that as a good compromise between the dual and quad-polarized SAR systems, the CP-SAR offer advantages in terms of the larger swath and lower data rate. The m − χ CP decomposition considers two out of the three Stokes child parameters: degree of polarization (m), ellipticity (χ), and orientation angle (ψ) to describe the polarized part of the quasi-monochromatic partially polarized wave. An improvement in the scattering powers was proposed in the S − Ω decomposition, which takes into accounts both the transmitted and received wave ellipticities (χ_t, χ_r) and the orientation angles (ψ_t, ψ_r). In this decomposition, S denotes the Stokes vector and Ω is the polarized power fraction. However, it may be noted that the S − Ω decomposition intrinsically ignores dominance in the target scattering mechanism while calculating the powers. In this work, improvement is proposed for the S − Ω decomposition by utilizing the degree of dominance in the scattering mechanism. The improved S − Ω (named as iS − Ω) decomposition powers are first compared with the existing m − χ and S − Ω powers for elementary (viz., trihedral and dihedral corner reflectors) and distributed targets using simulated CP-SAR data from quad-pol RADARSAT-2 data. An increase of ∼2% for odd and even-bounce powers obtained from the iS − Ω decomposition is observed for the trihedral and dihedral corner reflectors respectively. The analysis of the scattering powers for distributed targets shows that an increase of 15% and 12% in the even and odd-bounce powers is observed from iS − Ω for urban and bare soil areas respectively as compared to the m − χ and S − Ω decompositions. Besides, temporal variations in the scattering powers obtained from the iS − Ω decomposition are also analyzed for rice, cotton, and sugarcane crops at different growth stages.     

A new Likelihood Ratio for supervised classification of fully polarimetric SAR data: An application for sea ice type mapping

One of the potential applications of polarimetric Synthetic Aperture Radar (SAR) data is the classification of land cover, such as forest canopies, vegetation, sea ice types, and urban areas. In contrast to single or dual polarized SAR systems, full polarimetric SAR systems provide more information about the physical and geometrical properties of the imaged area. This paper proposes a new Bayes risk function which can be minimized to obtain a Likelihood Ratio (LR) for the supervised classification of polarimetric SAR data. The derived Bayes risk function is based on the complex Wishart distribution. Furthermore, a new spatial criterion is incorporated with the LR classification process to produce more homogeneous classes. The application for Arctic sea ice mapping shows that the LR and the proposed spatial criterion are able to provide promising classification results. Comparison with classification results based on the Wishart classifier, the Wishart Likelihood Ratio Test Statistic (WLRTS) proposed by Conradsen et al. (2003) and the Expectation Maximization with Probabilistic Label Relaxation (EMPLR) algorithm are presented. High overall classification accuracy of selected study areas which reaches 97.8% using the LR is obtained. Combining the derived spatial criterion with the LR can improve the overall classification accuracy to reach 99.9%. In this study, fully polarimetric C-band RADARSAT-2 data collected over Franklin Bay, Canadian Arctic, is used.     

顾及目标异质性的极化SAR图像非局部均值滤波

相干斑抑制是极化合成孔径雷达(Pol SAR)图像分析的重要预处理步骤。为了更好地抑制极化SAR图像中的相干斑,本文综合目标的异质性和结构信息,提出基于目标异质性的非局部均值滤波方法。首先利用K分布距离度量目标的异质性,并以异质性为基础,保留图像中的点、线等高异质性目标;然后计算图像块之间的异质性差异,最后将其作为度量非局部均值加权滤波像元相似性的权重系数,实现对Pol SAR图像的相干斑抑制。实验对比结果表明:本文方法能够有效地抑制相干斑,同时对细节信息和极化信息也具有良好的保持性,能够为后续的图像应用提供支持。     

A review of ground-based SAR interferometry for deformation measurement

This paper provides a review of ground-based SAR (GBSAR) interferometry for deformation measurement. In the first part of the paper the fundamentals of this technique are provided. Then the main data processing and analysis stages needed to estimate deformations starting from the GBSAR observations are described. This section introduces the two types of GBSAR acquisition modes, i.e., continuous and discontinuous GBSAR, and reviews the different GBSAR processing and analysis methods published in the literature. This is followed by a discussion of the specific technical aspects of GBSAR deformation measurement. A section then summarizes the pros and cons of GBSAR for deformation monitoring. The last part of the paper includes two reviews: one concerning the GBSAR systems described in the literature, including non-strictly SAR systems and a second one addresses the main GBSAR applications.     

多基线合成孔径雷达干涉相位估计方法探讨

针对多基线SAR干涉相位展开方法精度与效率之间难以兼顾的问题,文章提出一种高效稳健的相位展开方法:利用基于修正矩阵束模型的联合相位梯度估计技术快速和精确地从较短基线干涉图获取长基线干涉相位梯度,以增加算法的精度和效率;建立基于干涉图相干系数(或伪相干系数)以及相位微分偏差的相位质量图指导展开路径,以保证沿最优路径展开长基线干涉像元,有利于降低误差传递效应,提高相位展开精度;引入量化跟踪策略,减s少搜索最佳展开路径所消耗的时间,提高方法效率。仿真数据处理结果表明此方法具有精度及效率较高、稳健性较强的特点。     

一种改进的全极化SAR图像MCSM-Wishart非监督分类方法

针对H/Alpha/A-Wishart非监督分类算法存在的未充分提取SAR图像极化信息和分类精度低等问题,引入多分量散射模型(multiple-component scattering model,MCSM)分解,提出了一个适用于全极化SAR图像非监督分类的MCSM-Wishart算法。首先对全极化SAR图像进行MCSM分解,提取体散射、二次散射、螺旋体散射、表面散射和线散射极化信息,采用迭代自组织数据分析技术(iterative self-organizing data analysis technique,ISODATA)的非监督分类算法进行聚类;然后通过基于描述多视协方差矩阵的复Wishart分布的迭代分类得到分类结果。以南京溧水和盐城滨海湿地的ALOS PALSAR图像为研究数据,比较了H/Alpha-Wishart算法、H/Alpha/A-Wishart算法、MCSM-Wishart算法和监督-Wishart算法4种分类方法。研究结果表明,MCSM-Wishart分类算法在效率、总体准确率和Kappa系数等指标上均较原始分类器有一定的提高;将ISODATA聚类算法应用于复Wishart分布的迭代分类器中,可有效提高分类的精度。     

一种基于图像边缘特征的SAR斑点滤波算法

合成孔径雷达图像上的斑点噪声会阻碍图像的校准、检验、解译和应用,因此斑点噪声的去除是雷达图像处理的一个重要环节。通常的去噪方法在抑制噪声的同时也使得图像的边缘模糊,细节特征损失。理论和实践表明去除图像的斑点噪声和保持图像的边缘信息是无法同步实现的。为了在去除噪声和保持边缘特征之间进行折衷,本文基于MROA边缘检测算法以及均值滤波算法,提出了一种基于图像边缘特征的斑点噪声滤波算法。实验结果表明该算法能够在平滑图像的同时有效保持边缘特征信息。     

Glacier surface velocity estimation using SAR interferometry technique applying ascending and descending passes in Himalayas

In this study ascending and descending passes interferometric synthetic aperture radar (InSAR) techniques are used for glacier surface velocity estimation in the Himalaya. Single-track interferometric measurements are sensitive to only a single component of the three dimensional (3-D) velocity vectors. European Remote Sensing satellites (ERS-1/2) tandem mission data in ascending and descending tracks provide an opportunity to resolve the three velocity components under the assumption that glacier flow is parallel to its surface. Using the surface slope as an essential input in this technique the velocity pattern of Siachen glacier in Himalaya has been modelled. Glaciers in the Himalayan region maintain excellent coherence of SAR return signals in one-day temporal difference. As a result we could obtain spatially continuous surface velocity field with a precision of fraction of radar wavelength. The results covering the main course of glacier are analysed in terms of spatial and temporal variations. A maximum velocity of 43 cm/day has been observed in the upper middle portion of the glacier. This technique has been found accurate for monitoring the flow rates in this region, suggesting that routine monitoring of diurnal movement Himalayan glaciers would be immensely useful in the present day context of climate change.     

综合多特征的极化SAR图像随机森林分类算法

为抑制相干斑噪声对极化SAR图像分类结果的干扰,本文提出一种综合多特征的极化SAR图像随机森林分类方法。该方法首先利用简单线性迭代聚类(SLIC)算法生成超像素作为分类单元;然后,基于高维极化特征图像,利用训练好的随机森林模型,统计决策树的分类投票数,计算各超像素的类别概率;最后,利用超像素间的空间邻域特征,采用概率松弛算法(PLR)迭代修正超像素的类别后验概率,并依据最大后验概率(MAP)准则得到分类结果;实现综合利用超像素和空间邻域特征,降低相干斑噪声干扰的极化SAR图像分类方法。实验对比结果表明:本文方法能得有效抑制极化SAR图像中相干斑噪声的干扰,得到高精度且光滑连续的分类结果。     

ScanSAR干涉测量中的关键误差影响

ScanSAR模式具有宽观测带和重访时间短的优点,广泛应用于地表形变监测,在监测缓慢形变领域具有宽广的前景。ScanSAR干涉测量与条带干涉一样,降低基线误差和DEM残差影响是其主要瓶颈。本文分析了ScanSAR的成像原理及误差成因,针对Bam地震的ScanSAR干涉图,比较了SRTM3和GDEM在ScanSAR差分干涉中的影响大小,对采用3种不同精度的ENVISAT轨道数据得到的ScanSAR干涉结果进行了比较研究,研究结果可为相关领域提供参考。     

Maximum-likelihood estimation for multi-aspect multi-baseline SAR interferometry of urban areas

The reconstruction of digital surface models (DSMs) of urban areas from interferometric synthetic aperture radar (SAR) data is a challenging task. In particular the SAR inherent layover and shadowing effects need to be coped with by sophisticated processing strategies. In this paper, a maximum-likelihood estimation procedure for the reconstruction of DSMs from multi-aspect multi-baseline InSAR imagery is proposed. In this framework, redundant as well as contradicting observations are exploited in a statistically optimal way. The presented method, which is especially suited for single-pass SAR interferometers, is examined using test data consisting of experimental airborne millimeterwave SAR imagery. The achievable accuracy is evaluated by comparison to LiDAR-derived reference data. It is shown that the proposed estimation procedure performs better than a comparable non-statistical reconstruction method.     

基坑环境下建筑物沉降InSAR监测应用

针对近年来城市大建设背景下的基坑施工建设日益增多,对周边一定范围内的建筑物等目标产生影响的现象,该文提出面向单体建筑物的InSAR监测与应用方法。该方法基于时间序列的SAR影像进行面向对象的InSAR分析,在区分地面沉降与建筑物沉降的基础上,提取建筑物的沉降信息并结合基坑、建筑物特征等背景资料开展建筑物的灾害评估分析。以天津市和平区某基坑周边的渤海大楼为例,进行高分辨率的InSAR监测与应用分析,并以同步实测的水准数据为参考进行有效性评估。实验结果验证了该算法的有效性,适用于建筑物InSAR监测应用。     

结合凝聚层次聚类的极化SAR海冰分割

针对全极化高分辨率合成孔径雷达(SAR)多噪声的特点,选择合适的海冰SAR影像纹理特征量,并基于凝聚层次聚类的思想,提出一种全极化SAR海冰分割方法。将该方法的结果与K-Means、迭代自组织聚类(ISODATA)和模糊C均值算法等经典分割方法相比较,发现该方法的碎斑明显减少,且分割结果较为准确,证明了该方法的有效性。     

G0分布下基于白化滤波的极化SAR图像CFAR检测

在已有的极化合成孔径雷达(PolSAR)图像恒虚警(CFAR)检测方法中,存在着高分辨下杂波模型适用性差的难题。为解决此问题,提出了一种G_0分布下虚警概率具有闭合解析表达形式的CFAR检测方法,并定义虚警损失率(CFAR Loss, C_L)参数用以量化评估CFAR检测方法的恒虚警保持效果。首先,在乘积模型框架下,引入了逆Gamma纹理变量假设,推导出了多视极化白化滤波(MPWF)检测量的概率密度函数(PDF)。然后,对MPWF检测量的概率密度函数积分得到了虚警概率关于CFAR检测阈值的解析表达式,并设计了相应的CFAR检测流程。最后,采用仿真数据和AIRSAR实测数据对已有方法和新方法进行了算法运行时间、检测量拟合性能及目标检测性能对比。实验结果表明,方法运行时间比已有方法缩短3至30倍,具有良好的实时性;日本玉野地区的AIRSAR实测数据结果表明G_0分布对高分辨不均匀海区具有良好的拟合性能,且新方法在G_0分布和非G_0分布海区均能有效检测出目标,鲁棒性较强,相比其他检测方法品质因数(FoM)平均高出15.78%;C_L分析结果表明新方法具有良好的恒虚警保持性能,同时指出杂波对数累积量散点距离G_0分布曲线越近,新方法的恒虚警保持效果越好。