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Low rank modeling-based multipass InSAR technique

Kang, Jian and Wang, Yuanyuan and Zhu, Xiao Xiang (2018) Low rank modeling-based multipass InSAR technique. In: Proceedings of the European Conference on Synthetic Aperture Radar, EUSAR, pp. 1-6. EUSAR 2018, 04.-07. Juni 2018, Aachen, Germany.

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Official URL: http://conference.vde.com/eusar/2018/Pages/default.aspx


During the last few decades, multipass InSAR techniques have been developed for the retrieval of long term geophysical parameters, e.g. linear deformation rates, over large areas. Conventional method such as Persistent Scatter Interferometry (PSI) usually requires a fairly large SAR image stack (usually in the order of tens), in order to achieve reliable estimates of the parameters. However, in case of limited number of SAR images, e.g. less than 10, not only will the efficiency of the estimator decrease to an unacceptable level, the estimates will also suffer from large bias because of the asymptotic optimality of many typical estimators used in multipass InSAR, such as the periodogram used in PSI. In this paper, a novel multipass InSAR technique based on low rank modeling of complex-valued InSAR phase stacks is introduced. By combining this technique with PSI, we demonstrate that the proposed framework can improve the accuracy of geophysical parameters estimated via PSI by a factor of ten to thirty in typical settings, especially with a limited number of SAR images for the reconstruction.

Item URL in elib:https://elib.dlr.de/120031/
Document Type:Conference or Workshop Item (Speech)
Title:Low rank modeling-based multipass InSAR technique
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Wang, YuanyuanTUMhttps://orcid.org/0000-0002-0586-9413
Date:June 2018
Journal or Publication Title:Proceedings of the European Conference on Synthetic Aperture Radar, EUSAR
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In ISI Web of Science:No
Page Range:pp. 1-6
Keywords:low rank, tensor, robust estimation, multipass, multibaseline, InSAR, SAR
Event Title:EUSAR 2018
Event Location:Aachen, Germany
Event Type:international Conference
Event Dates:04.-07. Juni 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
Location: Oberpfaffenhofen
Institutes and Institutions:Remote Sensing Technology Institute > EO Data Science
Deposited By: Wang, Yuanyuan
Deposited On:24 May 2018 14:01
Last Modified:19 Jun 2018 00:37

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