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2010
Conference Paper
Titel
Detection of localized surface deformation using a modified StaMPS algorithm
Abstract
In recent years Persistent Scatterer Interferometry (PSI) has proven to be an operational tool for measuring surface deformation with up to millimetre accuracy. The two main ideas of PSI are the use of a stack of differential radar interferograms and the restriction to a set of temporally stable radar targets, the so called Persistent Scatterers. One approach to PSI analysis is the Stanford Method for Persistent Scatterers (StaMPS). We based our work mainly on this algorithm, in which assumptions are made about the statistical behaviour of the several phase contributions masking the deformation term. One of the basic ideas of this algorithm is to assess the temporal stability of the radar targets directly from the interferometric phase. However since the term representing phase noise is masked by several other terms like atmosphere or phase due to orbital inaccuracies, StaMPS uses an elaborate filtering procedure to remove all these phase contributions. Within this filtering procedure the deformation is assumed to be spatially correlated. That is a reasonable assumption for geophysical phenomena like surface movements due to volcanic activities. However if small localized deformations occur, the quality of targets undergoing localized deformation may be underestimated due to the interpretation of localized movements as phase noise. We modified StaMPS in order to cope with these localized movements and tested it on TerraSAR-X data. The test includes a corner reflector experiment, where several height adjustable corner reflectors were placed in the scene. While original StaMPS does not detect the localized movements correctly, the estimated deformation obtained using our modified StaMPS algorithm shows good agreement with the ground truth from our corner reflectors.
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