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An efficient algorithm for compressive sensing based SAR tomography

Shi, Yilei and Zhu, Xiao Xiang and Bamler, Richard and Yin, Wotao (2018) An efficient algorithm for compressive sensing based SAR tomography. In: Proceedings of the European Conference on Synthetic Aperture Radar, EUSAR, pp. 1-4. VDE Verlag. EUSAR 2018, 04.-07. June 2018, Aachen, Germany.

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Official URL: https://www.vde-verlag.de/proceedings-de/454636051.html

Abstract

Modern Tomographic SAR is an advanced InSAR techniques for urban mapping, which can not only retrieve 3D spatial information but also assess the 4D temporal information, such as deformation. To retrieve the information from InSAR data, several algorithms have been developed. Among them, SL1MMER algorithms is state of the art. However, it suffers from the computational expenses and it is hard to extend to large scale practice. In this work, we propose a novel optimization algorithms for L1 regularized least square in SL1MMER, which can keep the accuracy of the optimization result and dramatically speed up the processing.

Item URL in elib:https://elib.dlr.de/121497/
Document Type:Conference or Workshop Item (Speech)
Title:An efficient algorithm for compressive sensing based SAR tomography
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Shi, YileiTU-MünchenUNSPECIFIED
Zhu, Xiao XiangDLR-IMF/TUM-LMFUNSPECIFIED
Bamler, Richardrichard.bamler (at) dlr.deUNSPECIFIED
Yin, WotaoUCLAUNSPECIFIED
Date:4 June 2018
Journal or Publication Title:Proceedings of the European Conference on Synthetic Aperture Radar, EUSAR
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In SCOPUS:Yes
In ISI Web of Science:No
Page Range:pp. 1-4
Publisher:VDE Verlag
Status:Published
Keywords:Compressive Sensing, SAR tomography, TanDEM-X, SL1MMER, L1 regularization, randomized blockwise proximal gradient
Event Title:EUSAR 2018
Event Location:Aachen, Germany
Event Type:international Conference
Event Dates:04.-07. June 2018
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Erdbeobachtung
DLR - Research theme (Project):R - Vorhaben hochauflösende Fernerkundungsverfahren, R - SAR-Methodology
Location: Oberpfaffenhofen
Institutes and Institutions:Remote Sensing Technology Institute > EO Data Science
Remote Sensing Technology Institute > Leitungsbereich MF
Deposited By: Wang, Yuanyuan
Deposited On:29 Aug 2018 10:52
Last Modified:31 Jul 2019 20:19

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