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Improve multi-baseline InSAR parameter retrieval by semantic information from optical images

Kang, Jian and Wang, Yuanyuan and Körner, Marco and Zhu, Xiao Xiang (2017) Improve multi-baseline InSAR parameter retrieval by semantic information from optical images. In: 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), pp. 1-4. IEEE Xplore. IGARSS 2017, 23.-28. July 2017, Fort Worth, USA. doi: 10.1109/IGARSS.2017.8128244.

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One of the most unique benefits of multi-baseline synthetic aperture radar interferometry (InSAR) is the longterm monitoring of subtle ground deformation over large areas. Most state-of-the-art algorithms for retrieving such parameter are based on single pixels, e.g. Permanent Scatterer InSAR or clusters of ergodic pixels with stationary phases e.g. SqueeSAR. None of the studies has addressed the joint inversion in an object level, where the true interferometric phase may be varying subject to topography and deformation. Recently, one study has investigated SAR and optical data fusion in order to make use of the rich semantic information from optical images. Based on that work, we seek to investigate the possibility of an object-level multi-baseline InSAR deformation reconstruction given the semantic information from the corresponding optical images. In this paper, we introduced the tensor model for the multi-baseline InSAR inversion and proposed a maximum a posteriori estimator of the deformation parameters by including a spatial prior function in the objective function. Substantial improvement in the deformation estimation is observed in the experiments using both simulated and the real SAR data.

Item URL in elib:https://elib.dlr.de/112552/
Document Type:Conference or Workshop Item (Speech)
Title:Improve multi-baseline InSAR parameter retrieval by semantic information from optical images
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Zhu, Xiao Xiangdlr-imf/tum-lmfUNSPECIFIEDUNSPECIFIED
Journal or Publication Title:2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In ISI Web of Science:No
Page Range:pp. 1-4
Publisher:IEEE Xplore
Keywords:object-based, robust, low rank, PSI, multibaseline InSAR, InSAR
Event Title:IGARSS 2017
Event Location:Fort Worth, USA
Event Type:international Conference
Event Dates:23.-28. July 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:30 May 2017 16:11
Last Modified:25 Jul 2023 12:35

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