A tutorial on tomographic synthetic aperture radar methods

被引:9
|
作者
Khoshnevis, Seyed Alireza [1 ]
Ghorshi, Seyed [2 ]
机构
[1] Univ S Florida, Dept Elect Engn, Tampa, FL 33620 USA
[2] Univ Texas Tyler, Dept Elect Engn, Tyler, TX 75799 USA
来源
SN APPLIED SCIENCES | 2020年 / 2卷 / 09期
关键词
Synthetic aperture radar (SAR); Comperssive sensing (CS); Nonlinear least squares (NLS); Tomographic SAR (Tomo-SAR); Interferometric SAR (In-SAR); Singular value decomposition (SVD); SAR TOMOGRAPHY; BAND; INTERFEROMETRY;
D O I
10.1007/s42452-020-03298-6
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Synthetic Aperture Radar (SAR) is a type of radar that is mounted on an airborne platform and aims to increase the resolution of the acquisitions by traveling over the target area. The signals acquired by SAR are two dimensional, but it is possible to create three dimensional models using signal processing methods. Tomography is the method of creating three dimensional models from multiple two dimensional signals. This method can be applied to SAR acquisitions to create three dimensional models of the landscape. The goal of this study is to create a comprehensive tutorial on how to work with SAR data, what toolbox to use for analysis, how to create a tomographic SAR dataset, and how to use different methods of spectral estimation for SAR tomography. In this work, first, we focus on the main problem of SAR tomography followed by SAR preprocessing steps, a brief description of data levels, and finally, we discuss the different spectral estimation methods used in SAR tomography along with examples at every step.
引用
收藏
页数:14
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