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Robust object-based multipass InSAR deformation reconstruction

Kang, Jian and Wang, Yuanyuan and Körner, Marco and Zhu, Xiao Xiang (2017) Robust object-based multipass InSAR deformation reconstruction. IEEE Transactions on Geoscience and Remote Sensing, 55 (8), pp. 4239-4251. IEEE - Institute of Electrical and Electronics Engineers. DOI: 10.1109/TGRS.2017.2684424 ISSN 0196-2892

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Official URL: http://ieeexplore.ieee.org/abstract/document/7926387/?reload=true

Abstract

Deformation monitoring by multipass synthetic aperture radar (SAR) interferometry (InSAR) is, so far, the only imaging-based method to assess millimeter-level deformation over large areas from space. Past research mostly focused on the optimal retrieval of deformation parameters on the basis of a single pixel or a pixel cluster. Only until recently, the first demonstration of object-based urban infrastructure monitoring by fusing InSAR and the semantic classification labels derived from optical images was presented by Wang et al. Given such classification labels in the SAR image, we propose a general framework for object-based InSAR parameter retrieval, where the parameters of the whole object are jointly estimated by the inversion of a regularized tensor model instead of pixelwise. Our approach does not assume the stationarity of each sample in the object, which is usually assumed in other pixel cluster-based methods, such as SqueeSAR. In addition, to handle outliers in real data, a robust phase recovery step prior to parameter retrieval is also introduced. In typical settings, the proposed method outperforms the current pixelwise estimators, e.g., periodogram, by a factor of several tens in the accuracy of the linear deformation estimates. Last but not least, for a practical demonstration on bridge monitoring, we present a full workflow of long-term bridge monitoring using the proposed approach.

Item URL in elib:https://elib.dlr.de/114466/
Document Type:Article
Title:Robust object-based multipass InSAR deformation reconstruction
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Kang, JiantumUNSPECIFIED
Wang, Yuanyuantum, Yuanyuan.Wang (at) dlr.dehttps://orcid.org/0000-0002-0586-9413
Körner, Marcomarco.koerner (at) tum.deUNSPECIFIED
Zhu, Xiao Xiangdlr-imf/tum-lmfUNSPECIFIED
Date:11 May 2017
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:55
DOI :10.1109/TGRS.2017.2684424
Page Range:pp. 4239-4251
Publisher:IEEE - Institute of Electrical and Electronics Engineers
ISSN:0196-2892
Status:Published
Keywords:Bridge detection, joint deformation reconstruction, object-based, synthetic aperture radar (SAR), SAR interferometry
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 > SAR Signal Processing
Deposited By: Wang, Yuanyuan
Deposited On:13 Oct 2017 11:51
Last Modified:23 Feb 2019 00:21

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