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SAR Imaging via Modern 2-D Spectral Estimation Methods. Volume 1. Imaging Methods

机译：通过现代二维频谱估计方法进行saR成像。第1卷。成像方法

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This report discusses the use of modern 2-D spectral estimation algorithms forSAR imaging, and makes two principal contributions to the field of adaptive SAR imaging. First, it is a comprehensive comparison of 2-D spectral estimation methods for SAR imaging. It provides a synopsis of the algorithms available, discusses their relative merits for SAR imaging, and illustrates their performance on simulated and collected SAR imagery. The discussion of autoregressive linear predictive techniques (ARLP), including the Tufts Kumaresan variant, is somewhat more general than appears in most of the literature, in that it allows the prediction element to be varied throughout the subaperture. This generality leads to a theoretical link between ARLP and one of Pisarenko's methods. The report also provides a theoretical analysis that predicts the impact of the adaptive sidelobe reduction (ASR) algorithm on target to clutter ratio and provides insight into order and constraint selection. Second, this work develops multi-channel variants of three related algorithms, minimum variance method (MVM), reduced rank MVM (RRMVM), and ASR to estimate both reflectivity intensity and interferometric height from polarimetric displaced-aperture interferometric data. Examples illustrate that MVM and ASR both offer significant advantages over Fourier methods for estimating both scattering intensity and interferometric

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作者
DeGraaf, S. R.;
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年度 1995
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总页数 55
原文格式 PDF
正文语种 eng
中图分类工业技术;
关键词
Synthetic aperture radar; Radio interferometry; Algorithms; Linear systems; Comparison; Intensity; Electromagnetic scattering; Radar images; Mathematical prediction; Adaptive systems; Radar clutter; Reflectivity; Sidelobes; Fourier analysis; Rank order st;

机译：合成孔径雷达;无线电干涉测量;算法;线性系统;比较;强度;电磁散射;雷达图像;数学预测;自适应系统;雷达杂波;反射率;旁瓣;傅立叶分析;秩序st;

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专利

1. SAR imaging via modern 2-D spectral estimation methods [J] . DeGraaf S.R. IEEE Transactions on Image Processing . 1998,第5期

机译：通过现代二维光谱估计方法进行SAR成像
2. High-Throughput Label-Free Detection Using a Gold Nanoslit Array With 2-D Spectral Images and Spectral Integration Methods [J] . Lee K.-L., Tsai J.-T., Chih M.-J., Selected Topics in Quantum Electronics, IEEE Journal of . 2013,第3期

机译：使用具有二维光谱图像和光谱积分方法的金纳米狭缝阵列进行高通量无标记检测
3. Comparing the performance of a 2-D finite element and a 2-D finite volume model of flood plain inundation using airborne SAR imagery [J] . M. S. Horritt, G. Di Baldassarre, P. D. Bates, Hydrological Processes . 2007,第20期

机译：利用机载SAR图像比较洪泛平原淹没的二维有限元模型和二维有限体积模型的性能
4. SAR imaging via modern 2D spectral estimation methods [C] . Stuart R. DeGraaf, Environmental Research Institute of Michigan, Ann Arbor, Conference on algorithms for synthetic aperture radar imagery . 1994

机译：通过现代2D光谱估计方法进行SAR成像
5. Hyperspectral Image Classification with Nonlinear Methods. [D] . Liu, Tiancheng. 2016

机译：非线性方法的高光谱图像分类。
6. Estimation of Melanin and Hemoglobin Using Spectral Reflectance Images Reconstructed from a Digital RGB Image by the Wiener Estimation Method [O] . Izumi Nishidate, Takaaki Maeda, Kyuichi Niizeki, 2013

机译：使用维纳估计法从数字RGB图像重建的光谱反射图像估计黑色素和血红蛋白
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SAR Imaging via Modern 2-D Spectral Estimation Methods. Volume 1. Imaging Methods

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