%0 Journal Article
%T Modeling high-resolution synthetic aperture radar images with heavy-tailed distributions<br>基于拖尾分布的高分辨率合成孔径雷达图像建模
%A Sun Zeng-Guo
%A Han Chong-Zhao
%A <br>孙增国
%A 韩崇昭
%J 物理学报
%D 2010
%I 
%X Statistical distributions of synthetic aperture radar (SAR) images based on central limit theorem cannot reflect the statistical characteristics of sharp peak and heavy tail of high-resolution SAR images. By using the generalized central limit theorem,the heavy-tailed distributions (heavy-tailed Rayleigh distribution for amplitude image and heavy-tailed exponential distribution for intensity image) are obtained from the symmetric stable distributions of real and imaginary parts of echoes. Taking the heavy-t...
%K high-resolution synthetic aperture radar images
%K generalized central limit theorem
%K heavy-tailed distributions
%K log-cumulant estimator<br>高分辨率合成孔径雷达图像，广义中心极限定理，拖尾分布，对数累积量估计
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=6E709DC38FA1D09A4B578DD0906875B5B44D4D294832BB8E&cid=47EA7CFDDEBB28E0&jid=29DF2CB55EF687E7EFA80DFD4B978260&aid=3C23BB1740863ACB566CA465AB406522&yid=140ECF96957D60B2&vid=6AC2A205FBB0EF23&iid=0B39A22176CE99FB&sid=EAA944F99AA73B33&eid=82BCA4C44409DD5C&journal_id=1000-3290&journal_name=物理学报&referenced_num=0&reference_num=0