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用多方向飞行的全极化SAR图像可能提取特定三维目标的高度与位置信息,进而实现目标物的几何立体重构。全极化SAR图像数据与单极化SAR相比,可以选择多种极化组合数据,提供对于特定目标几何特征敏感的数据类型,通过多方向飞行SAR图像反演该目标或目标群的高度与位置信息。本文用两幅相向飞行的PI-SAR(日本机载极化与干涉SAR,X波段、1.5m分辨率)图像,提取日本仙台电视塔高度、日本东北大学建筑物群的立体重构。 相似文献
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Interference suppression in synthesized SAR images 总被引:4,自引:0,他引:4
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Single, interferometric dual, and quad-polarization mode data were evaluated for the characterization and classification of seven land use classes in an area with shifting cultivation practices located in the Eastern Amazon (Brazil). The Advanced Land-Observing Satellite (ALOS) Phased Array L-band Synthetic Aperture Radar (PALSAR) data were acquired during a six month interval. A clear-sky Landsat-5/TM image acquired at the same period was used as additional ground reference and as ancillary input data in the classification scheme. We evaluated backscattering intensity, polarimetric features, interferometric coherence and texture parameters for classification purposes using support vector machines (SVM) and feature selection. Results showed that the forest classes were characterized by low temporal backscattering intensity variability, low coherence and high entropy. Quad polarization mode performed better than dual and single polarizations but overall accuracies remain low and were affected by precipitation events on the date and prior SAR date acquisition. Misclassifications were reduced by integrating Landsat data and an overall accuracy of 85% was attained. The integration of Landsat to both quad and dual polarization modes showed similarity at the 5% significance level. SVM was not affected by SAR dimensionality and feature selection technique reveals that co-polarized channels as well as SAR derived parameters such as Alpha-Entropy decomposition were important ranked features after Landsat’ near-infrared and green bands. We show that in absence of Landsat data, polarimetric features extracted from quad-polarization L-band increase classification accuracies when compared to single and dual polarization alone. We argue that the joint analysis of SAR and their derived parameters with optical data performs even better and thus encourage the further development of joint techniques under the Reducing Emissions from Deforestation and Degradation (REDD) mechanism. 相似文献
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《Geoscience and Remote Sensing Letters, IEEE》2009,6(3):408-412
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极化SAR干涉测量模拟研究 总被引:2,自引:0,他引:2
极化SAR干涉测量将极化测量技术和干涉测量技术巧妙地结合,能够提高干涉测量精度,尤其是在植被覆盖的情况下,不仅能够测量地表地形,而且使得估计植被高度成为可能。因此,近几年来国际上对极化SAR干涉测量技术的研究越来越重视,极化SAR干涉测量已成为SAR应用技术发展的重要方向。通过模拟技术深入研究极化SAR干涉测量理论和方法,并提出了一种新的极化SAR干涉测量改进算法,模拟实验结果表明,该算法可以进一步提高测量精度。 相似文献
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极化干涉SAR数据地表土地类型分类 总被引:2,自引:0,他引:2
基于新疆和田地区1994年10月9日和10日SIR-C-L波段全极化雷达数据。首先对极化干涉测量的基本原理和数据处理流程进行了详细的阐述,接着,用Cloude相干最优算法得到了与3种地物散射机制相对应的3个最优相干图。并且就地物相干性对极化的强烈依赖和3种散射机制中地物的最优相干特性进行了分析,具有最高相干值的相位图在提取DEM方面较有利,具有最低相干值的相干图在地物识别方面较有利。最后,在对最优相干系数。后向散射系数和熵进行数据相关性分析基础上,利用得到的最优相干系数,熵和后向散射系数数据进行了土地类型的识别和分类,得到了很好的效果。 相似文献
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ERPRIT算法估计的地表散射相位由于易受到森林去极化成分的影响而出现较大的偏差,从而导致植被高度反演结果严重偏低.针对这一问题,本文提出一种基于散射机制分解的ESPRIT植被高度反演算法.该算法关键点是利用Freeman分解理论和极化干涉互协方差矩阵估计得到更加准确的地表散射相位,以替代ESPRIT算法估计的地表散射相位,进而改善植被高度反演的精度.最后,分别利用欧空局(ESA)免费发布的PolSARpro软件模拟L波段极化干涉合成孔径雷达数据和PALSAR真实星载数据验证改进算法的有效性. 相似文献
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Estimation of the polarization orientation angle shifts induced by terrain azimuth slope variations is a recently developed application in radar polarimetry. In general, without any prior knowledge on the terrain, two polarimetric SAR (POLSAR) flight passes are required to derive terrain slopes in perpendicular directions for digital elevation model (DEM) generation. Moreover, we note that SAR intensity is a strong indicator of the range component of the terrain slopes. In this letter, we developed a method for DEM generation requiring only one POLSAR flight pass, by combining orientation angle estimation and a shape-from-shading technique. In particular, when limited POLSAR data are available, this POLSAR technique provides an alternative way for DEM generation. National Aeronautics and Space Administration Jet Propulsion Laboratory (NASA/JPL) AIRSAR L-band POLSAR data over Camp Roberts, California, is used to demonstrate the results of the method proposed in this letter, and a DEM derived from simultaneously measured C-band interferometric SAR from NASA/JPL topographic SAR instrument is selected as the comparative ground truth to validate the effectiveness of this single POLSAR method. Analyses and discussions are also included in this letter. 相似文献
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针对经典极化分类算法在处理机载X波段SAR数据时将过多地物分为体散射类型,并且容易受噪声影响,分类结果存在大量误分现象的问题,通过对机载X波段SAR数据非监督分类方法的研究,提出将极化干涉信息用于机载X波段极化干涉SAR数据的分类。通过运用极化干涉数据进行目标分解得到参数A1和A2对数据进行初始分类,然后结合改进的Wishart最大似然分类算法来进行地物的自适应分类。实验结果表明,该方法能有效避免平地效应的影响,抗噪性好,能正确区分三种典型散射类型,分类效果明显优于极化分类效果。 相似文献
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Topography-dependent motion compensation for repeat-pass interferometric SAR systems 总被引:3,自引:0,他引:3
This letter presents a new motion compensation algorithm to process airborne interferometric repeat-pass synthetic aperture radar (SAR) data. It accommodates topography variations during SAR data processing, using an external digital elevation model. The proposed approach avoids phase artifacts, azimuth coregistration errors, and impulse response degradation, which usually appear due to the assumption of a constant reference height during motion compensation. It accurately modifies phase history of all targets before azimuth compression, resulting in an enhanced image quality. Airborne L-band repeat-pass interferometric data of the German Aerospace Center experimental airborne SAR (E-SAR) is used to validate the algorithm. 相似文献
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From repeat pass SIR-C L band polarimetric SAR interferometric data and fully maximum likelihood inversion decomposition model of PolInSAR, a method for sub-canopy soil moisture estimation using repeat pass SIR-C PolInSAR data is proposed. At the same time, the potential and validity of fully maximum likelihood inversion decomposition model of PolInSAR for sub-canopy soil moisture inversion is investigated. Firstly, from the random oriented volume over ground two layer coherent scattering model and the statistical characteristics of Pol-InSAR coherency matrix, the fully maximum likelihood inversion decomposition model is used to reconstruct or recover the surface polarimetric coherency matrix with volume scattering components significantly removed; then, from recovered surface polarimetric coherency matrix, co-HH, VV and cross-HV polarization backscattering coefficient are obtained, and the sub-canopy soil moisture are inverted from Oh and Dihedral scattering model. At last, Compared the inversion result with the field measurement and the climate data of hetan region from 1951 to 2006, the preliminary result indicates that the proposed method based on fully maximum likelihood inversion decomposition model has enough high inversion accuracy, if the new spaceborne or airborne polarimetric SAR interferometric data with synchronously spaceborne or airborne-ground measurement will be acquired, the validity and accuracy of proposed inversion method will be further investigated and validated. 相似文献
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基于MODIS影像的森林火灾火线检测方法 总被引:1,自引:0,他引:1
结合归一化火灾差异指数NDBR(normalized difference burn ratio)和MODIS多波段影像梯度边缘分析手段检测火线, 应用B样条函数拟合火线并确定火势蔓延方向。为对比验证, 基于火线的Kriging插值实现火灾外推预测, 与30min后的火灾参考数据目视对比与统计:火线的预测变化与参考影像基本保持一致, 火灾外推影像的均值和熵约为参考影像的86%和81%, 火迹地检测的Kappa系数达80.2%。试验表明, 提出的森林火线特征自动检测方法在动态火灾监测中是可行、有效的。 相似文献
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This letter analyzes different approaches for polarimetric optimization of multibaseline (MB) interferometric coherences. Two general methods are developed to simultaneously optimize coherences for more than two data sets. The first method provides every data set with a distinct dominant scattering mechanism (SM). The second optimization method is constrained to use equal SMs at all data sets. As the experimental results indicate, MB coherence optimization does improve the accuracy in the estimation of dominant SMs and the associated interferometric phases. Both methods are evaluated on real data acquired by the German Aerospace Agency (DLR)'s enhanced synthetic aperture radar sensor (ESAR) at L-band. 相似文献
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经典三阶段极化干涉SAR植被高反演算法中地面散射相位估计不准确,从而导致植被高反演精度存在偏差。针对这一关键问题,本文提出基于极化干涉互协方差矩阵分解的植被高度反演新方法。该方法利用Freeman分解理论和极化干涉互协方差矩阵,估计出更准确的地面散射相位;然后,结合RVOG模型反演植被高度。利用欧空局(ESA)的软件PolSARpro模拟的L波段极化SAR数据和亚马逊森林地区的ALOS PALSAR L波段数据进行实验,结果表明本文提出的新算法提取的植被高度相比经典三阶段法精度更高,从而验证了算法的有效性和可靠性。 相似文献
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P. V. Jayasri K. Niharika Manoj Joseph H. S. V. Usha Sundari Ryali C. V. Ramana Sarma E. V. S. Sita Kumari A. V. V. Prasad 《Journal of the Indian Society of Remote Sensing》2018,46(6):1005-1012
With recent advances in polarimetry, Synthetic Aperture Radar (SAR) with Hybrid–polarity architecture, a demonstration of compact polarimetry enabled larger swath coverage, reduced PRF and SAR system complexity as compared to fully polarimetric systems. The first Hybrid Polarimetric Space-borne SAR in Earth Observation orbit, India’s Radar Imaging Satellite (RISAT-1) is a new-fangled gateway to remote sensing user community for land and oceanic applications. In response to a right-circular polarized transmitted signal, based on the derived stokes vectors, Stokes parameters are estimated to produce several useful quantitative measures for generating polarimetric decomposed image. m-delta, m-chi and m-alpha polarimetric decomposition methods along with suitable weighting functions in terms of three principal components are implemented which maps Stokes parameters to RGB image space for representing odd bounce, even bounce and volume scattering targets. Various RISAT-1 Hybrid Fine Resolution Stripmap Single-Look Complex SAR datasets acquired over deployed corner reflectors at calibration site, Shadnagar have been considered over which different hybrid polarimetric decomposition techniques are implemented using in-house developed software. Further analysis produced encouraging results with standard point targets like dihedral and trihedral corner reflectors against distributed targets in the same scene to demonstrate the scattering mechanisms as per their characteristics when interacted with a polarized signal were presented in this paper. 相似文献
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森林的高度和垂直结构剖面都是重要的森林空间结构信息,极化干涉SAR的出现使定量获取森林结构参数成为可能。在分析比较三阶段法、DEM差分法和相干幅度法估计森林高度的基础上,采用相干幅度算法提取的树高,通过勒让德多项式展开以及单基线极化干涉数据提取森林的垂直结构剖面。利用仿真SAR数据进行实验分析,研究表明,通过极化相干层析技术,能够获取准确的森林垂直结构函数。 相似文献
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The objective of this study is to efficiently extract detailed information about various man-made targets in oriented built-up areas using polarimetric synthetic aperture radar (POLSAR) images. This paper develops an improved approach for building detection by utilizing Two-Dimensional Time-Frequency (2-D TF) decomposition. This method performs outstandingly in distinguishing between man-made and natural targets based on the isotropic behaviors, frequency-sensitive responses, and scattering mechanisms of objects. The proposed method can preserve the spatial resolution and exploit the advantages of TF decomposition; specifically, the exact outlines of buildings can be effectively located, and more types of features (e.g., flat roofs, roads, and walls that are oblique to the radar illumination) can be distinguished from forests in complex built-up areas by 2-D TF decomposition. The coarser-resolution subaperture images that are produced in the azimuth direction, which correspond to different looking angles, are beneficial for detecting man-made structures with main scattering centers oriented at oblique angles with respect to the radar illumination. In the range direction, the obtained subaperture images, which correspond to various observation frequencies, can be helpful in distinguishing flat roofs and roads from forests. This method was successfully implemented to analyze both NASA/JPL L-band AIRSAR and L-band EMISAR data sets. The building detection results of the proposed method exhibit a significant improvement over those of other methods and reach an overall accuracy over 80%, with approximately 20% higher than the accuracies of K-means clustering and the entropy/alpha-Wishart classifier and approximately 10% higher than the accuracy of the support vector machine method. Moreover, building details can be precisely detected, obliquely oriented buildings can be identified, and the distinction between buildings and forests is significantly improved, as both visually and statistically indicated. This method is highly adaptable and has substantial application value. 相似文献
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基于Freeman_Durden分解的全极化SAR影像分类方法能够较好地保持地物极化散射特性,但在分类的过程中,不能改变初始散射机制,导致分解结果对分类精度影响很大。在Freeman_Durden分解中,排列方向相对雷达飞行方向不平行的建筑物(简称为倾斜建筑物)常被分为体散射类型,使得该类建筑物往往被误分为植被。通过分析建筑物在SAR影像中的后向散射特性,利用建筑物具有较高相干性的特点,引入最优极化相干系数,在目标分解的基础上通过阈值分割将两者区分开来,进而提高反射非对称性人工目标的分类效果。通过使用E-SAR系统在德国DLR附近Oberp-faffenhofen地区获取的L波段PolInSAR影像和国内X-SAR系统在海南陵水地区获取的X波段PolInSAR影像进行试验,证明该方法能够有效地将与雷达飞行方向不平行的建筑物与森林区分开。 相似文献