DLR-Logo -> http://www.dlr.de
DLR Portal Home | Imprint | Privacy Policy | Contact | Deutsch
Fontsize: [-] Text [+]

The robust InSAR optimization framework with application to monitoring cities on volcanoes

Wang, Yuanyuan and Zhu, Xiao Xiang (2015) The robust InSAR optimization framework with application to monitoring cities on volcanoes. In: Joint Urban Remote Sensing Event (JURSE) 2015, pp. 1-4. IEEE Xplore. JURSE 2015, 30 March - 1 April 2015, Lausanne, Switzerland. doi: 10.1109/JURSE.2015.7120466.

[img] PDF

Official URL: http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7120466


This paper introduces the Robust InSAR Optimization (RIO) framework to the multi-pass InSAR techniques, such as PSI, SqueeSAR and TomoSAR whose current optimal estimators were derived based on the assumption of Gaussian distributed stationary data, with seldom attention towards their robustness. The RIO framework effectively tackles two common problems in the multi-pass InSAR techniques: 1. treatment of images with bad quality, especially those with large uncompensated atmospheric phase, and 2. the covariance matrix estimation of non-stationary distributed scatterer (DS). The former problem is dealt with using a robust M-estimator which effectively down-weight the images that heavily violate the model, and the latter is addresses with a new method: the Rank M-Estimator (RME) by which the covariance is estimated using the rank of the DS. RME requires no flattening/estimation of the interferometric phase, thanks to the property of mean invariance of rank. The robustness of RME is achieved by using an M-estimator, i.e. amplitude-based weighing function in covariance estimation. The RIO framework can be easily extended to most of the multi-pass InSAR techniques.

Item URL in elib:https://elib.dlr.de/100016/
Document Type:Conference or Workshop Item (Speech)
Title:The robust InSAR optimization framework with application to monitoring cities on volcanoes
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Journal or Publication Title:Joint Urban Remote Sensing Event (JURSE) 2015
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:robust estimation, M-estimator, rank covariance matrix, D-InSAR, InSAR
Event Title:JURSE 2015
Event Location:Lausanne, Switzerland
Event Type:international Conference
Event Dates:30 March - 1 April 2015
Organizer:IEEE Org.
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:26 Nov 2015 15:54
Last Modified:31 Jul 2019 19:56

Repository Staff Only: item control page

Help & Contact
electronic library is running on EPrints 3.3.12
Website and database design: Copyright © German Aerospace Center (DLR). All rights reserved.