Robust TomoSAR focusing for forest height retrieval

H. Aghababaee, G. Ferraioli, V. Pascazio, Gilda Schirinzi
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Abstract

This paper aims to discuss and present analysis on robust reconstruction of vertical structure of forested area suing multi-baseline synthetic aperture radar (SAR) data. To deal with problem of low signal to noise (SNR) ratio, robust non-local (NL) techniques of covariance matrix estimation are employed and compared with classical multi-looking approaches. The analysis will consider the quality of the vertical structure profile in such a way to cover the reconstruction quality using both single and fully polarimetric MB data sets. To evaluate the three-dimensional imaging of volumetric media in case of fully polarimetric images, the sum of Kronecker product (SKP) of covariance matrix in which polarization is considered as a way to discriminate the vertically aligned scatterers. From the experimental results, the impact of NL neighborhoods in robust estimation of covariance matrix to resolve the interference signals (e.g. layover) is the most relevant conclusion of the paper.
鲁棒TomoSAR聚焦森林高度检索
本文旨在探讨和分析利用多基线合成孔径雷达(SAR)数据进行林区垂直结构鲁棒重建的方法。为了解决低信噪比的问题,采用了鲁棒非局部协方差矩阵估计技术,并与经典的多视方法进行了比较。分析将以这样一种方式考虑垂直结构剖面的质量,以涵盖使用单一和全偏振MB数据集的重建质量。为了评价在完全极化成像情况下体介质的三维成像效果,将极化作为区分垂直排列散射体的一种方式,计算协方差矩阵的Kronecker积(SKP)和。从实验结果来看,NL邻域对协方差矩阵鲁棒估计解决干扰信号(如中途停留)的影响是本文最相关的结论。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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