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Robust object-based multi-baseline InSAR

Kang, Jian and Wang, Yuanyuan and Körner, Marco and Zhu, Xiao Xiang (2017) Robust object-based multi-baseline InSAR. In: FRINGE 2017, pp. 1-9. FRINGE 2017, 5.-9. Juni 2017, Helsinki, Finland.

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Deformation monitoring by multi-baseline repeat-pass synthetic aperture radar (SAR) interferometry 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 deformation parameters retrieval on a pixel-basis. Only until recently, the first demonstration of object-based urban infrastructures monitoring by fusing SAR interferometry (InSAR) and the semantic classification labels derived from optical images was presented in [1]–[3]. This paper demonstrates a general framework for object-based InSAR parameters retrieval where the estimation of the parameters is achieved in an object-level instead of pixel-wisely. Furthermore, to handle outliers in real data, a robust phase recovery step in prior to the parameters inversion is also introduced. The proposed method outperforms the current pixel-wised estimators, e.g. periodogram, by a factor of as much as several dozens in the accuracy of the linear deformation estimates. [1] Y. Wang and X. X. Zhu, “Fusing Meter-Resolution 4-D InSAR Point Clouds and Optical Images for Semantic Urban Infrastructure Monitoring,” IEEE Trans. Geosci. Remote Sens., 2016. [2] Y. Wang and X. X. Zhu, “InSAR Forensics: Tracing InSAR Scatterers in High Resolution Optical Image,” presented at the Fringe 2015, 2015. [3] Y. Wang and X. X. Zhu, “Semantic Fusion of SAR Interferometry and Optical Image with Application to Urban Infrastructure Monitoring,” presented at the CMRT, France, La Grande Motte, France, 2015.

Item URL in elib:https://elib.dlr.de/113970/
Document Type:Conference or Workshop Item (Speech)
Title:Robust object-based multi-baseline InSAR
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Wang, YuanyuantumUNSPECIFIED
Körner, Marcomarco.koerner (at) tum.deUNSPECIFIED
Zhu, Xiao Xiangdlr-imf/tum-lmfUNSPECIFIED
Journal or Publication Title:FRINGE 2017
Refereed publication:No
Open Access:Yes
Gold Open Access:No
In ISI Web of Science:No
Page Range:pp. 1-9
Keywords:Object-based, deformation, InSAR, PSI, TomoSAR
Event Title:FRINGE 2017
Event Location:Helsinki, Finland
Event Type:international Conference
Event Dates:5.-9. Juni 2017
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)
Location: Oberpfaffenhofen
Institutes and Institutions:Remote Sensing Technology Institute > SAR Signal Processing
Deposited By: Wang, Yuanyuan
Deposited On:13 Sep 2017 13:29
Last Modified:31 Jul 2019 20:11

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