@inproceedings{2c454084887047218d114be19c832aa8,
title = "Robust TomoSAR focusing for forest height retrieval",
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.",
keywords = "Covariance matrix, NL-SAR, SAR tomography, Vertical structure of forest, ITC-CV",
author = "Hossein Aghababaee and Giampaolo Ferraioli and Vito Pascazio and Gilda Schirinzi",
year = "2018",
month = jun,
day = "13",
doi = "10.1109/EE1.2018.8385271",
language = "English",
series = "2018 IEEE International Conference on Environmental Engineering, EE 2018 - Proceedings",
publisher = "IEEE",
pages = "1--5",
booktitle = "2018 IEEE International Conference on Environmental Engineering, EE 2018 - Proceedings",
address = "United States",
note = "2018 IEEE International Conference on Environmental Engineering, EE 2018 ; Conference date: 12-03-2018 Through 14-03-2018",
}