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Single-Look Multi-Master SAR Tomography: An Introduction

Ge, Nan and Bamler, Richard and Hong, Danfeng and Zhu, Xiao Xiang (2021) Single-Look Multi-Master SAR Tomography: An Introduction. IEEE Transactions on Geoscience and Remote Sensing, 59 (3), pp. 2132-2154. IEEE - Institute of Electrical and Electronics Engineers. doi: 10.1109/TGRS.2020.3002945. ISSN 0196-2892.

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Official URL: https://ieeexplore.ieee.org/document/9133203

Abstract

This article addresses the general problem of single-look multi-master SAR tomography. For this purpose, we establish the single-look multi-master data model, analyze its implications for the single and double scatterers, and propose a generic inversion framework. The core of this framework is the nonconvex sparse recovery, for which we develop two algorithms: one extends the conventional nonlinear least squares (NLS) to the single-look multi-master data model and the other is based on bi-convex relaxation and alternating minimization (BiCRAM). We provide two theorems for the objective function of the NLS subproblem, which lead to its analytic solution up to a constant phase angle in the 1-D case. We also report our findings from the experiments on different acceleration techniques for BiCRAM. The proposed algorithms are applied to a real TerraSAR-X data set and validated with the height ground truth made available by an SAR imaging geodesy and simulation framework. This shows empirically that the single-master approach, if applied to a single-look multi-master stack, can be insufficient for layover separation, and the multi-master approach can indeed perform slightly better (despite being computationally more expensive) even in the case of single scatterers. In addition, this article also sheds light on the special case of single-look bistatic SAR tomography, which is relevant for the current and future SAR missions such as TanDEM-X and Tandem-L.

Item URL in elib:https://elib.dlr.de/138973/
Document Type:Article
Title:Single-Look Multi-Master SAR Tomography: An Introduction
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Ge, NanNan.Ge (at) dlr.deUNSPECIFIED
Bamler, RichardRichard.Bamler (at) dlr.deUNSPECIFIED
Hong, DanfengDanfeng.Hong (at) dlr.deUNSPECIFIED
Zhu, Xiao Xiangxiao.zhu (at) dlr.deUNSPECIFIED
Date:March 2021
Journal or Publication Title:IEEE Transactions on Geoscience and Remote Sensing
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In SCOPUS:Yes
In ISI Web of Science:Yes
Volume:59
DOI :10.1109/TGRS.2020.3002945
Page Range:pp. 2132-2154
Publisher:IEEE - Institute of Electrical and Electronics Engineers
ISSN:0196-2892
Status:Published
Keywords:Bistatic SAR, nonconvex optimization, SAR tomography, sparse recovery, synthetic aperture radar (SAR), Tandem-L, TanDEM-X.
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Earth Observation
DLR - Research theme (Project):R - Vorhaben hochauflösende Fernerkundungsverfahren (old), R - SAR methods
Location: Oberpfaffenhofen
Institutes and Institutions:Remote Sensing Technology Institute > EO Data Science
Remote Sensing Technology Institute > Leitungsbereich MF
Deposited By: Liu, Rong
Deposited On:03 Dec 2020 16:50
Last Modified:01 Mar 2021 16:23

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