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Tomographic SAR Inversion by L1 Norm Regularization – The Compressive Sensing Approach

Zhu, Xiao Xiang and Bamler, Richard (2010) Tomographic SAR Inversion by L1 Norm Regularization – The Compressive Sensing Approach. IEEE Transactions on Geoscience and Remote Sensing, 48 (10), pp. 3839-3846. DOI: 10.1109/TGRS.2010.2048117 . ISSN 0196-2892 .

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Official URL: http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5482209&tag=1

Abstract

SAR tomography (TomoSAR) extends the synthetic aperture principle into the elevation direction for 3-D imaging. The resolution in the elevation direction depends on the size of the elevation aperture, i.e. on the spread of orbit tracks. Since the orbits of modern meter-resolution space-borne SAR systems, like TerraSAR-X, are tightly controlled, the tomographic elevation resolution is at least an order of magnitude lower than in range and azimuth. Hence, super-resolution reconstruction algorithms are desired. The high anisotropy of the 3D tomographic resolution element renders the signals sparse in the elevation direction; only a few point-like reflections are expected per azimuth-range cell. This property suggests using compressive sensing (CS) methods for tomographic reconstruction. The paper presents the theory of 4-D (differential, i.e. space-time) CS TomoSAR and compares it with parametric (nonlinear least-squares) and non-parametric (singular value decomposition) reconstruction methods. Super-resolution properties and point localization accuracies are demonstrated using simulations and real data. A CS reconstruction of a building complex from TerraSAR-X spotlight data is presented.

Document Type:Article
Title:Tomographic SAR Inversion by L1 Norm Regularization – The Compressive Sensing Approach
Authors:
AuthorsInstitution or Email of Authors
Zhu, Xiao XiangTUM
Bamler, RichardUNSPECIFIED
Date:2010
Journal or Publication Title:IEEE Transactions on Geoscience and Remote Sensing
Refereed publication:Yes
In Open Access:No
In SCOPUS:Yes
In ISI Web of Science:Yes
Volume:48
DOI:10.1109/TGRS.2010.2048117
Page Range:pp. 3839-3846
ISSN:0196-2892
Status:Published
Keywords:Differential SAR tomography, compressive sensing, urban mapping, TerraSAR-X
HGF - Research field:Aeronautics, Space and Transport (old)
HGF - Program:Space (old)
HGF - Program Themes:W EO - Erdbeobachtung
DLR - Research area:Space
DLR - Program:W EO - Erdbeobachtung
DLR - Research theme (Project):W - Vorhaben SAR-Expert-Support-Lab (old)
Location: Oberpfaffenhofen
Institutes and Institutions:Remote Sensing Technology Institute > SAR Signal Processing
Deposited By: Xiao Xiang Zhu
Deposited On:25 Oct 2010 13:18
Last Modified:04 Apr 2013 16:17

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