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Proceedings Paper

Phase unwrapping methods of corner reflector DInSAR monitoring slow ground deformation
Author(s): Wenxue Fu; Xiaofang Guo; Qingjiu Tian
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Paper Abstract

Difference interferometric Synthetic aperture radar (DInSAR) has turned out to be a very powerful technique for the measurement of land deformations, but it requires the observed area to be correlated, and coherence degradation will seriously affect the quality of interferogram. Corner reflector DInSAR (CRDInSAR) is a new technique in recently years, which can compensate for the limitation of the classical DInSAR. Due to the stable amplitude and phase performance of the reflector, the interferometric phase difference of the reflector can be used to monitor or measure the small and slowly ground deformation for the cases of large geometrical baseline and large time interval between acquisitions. Phase unwrapping is the process where the absolute phase is reconstructed from its principal value as accurately as possible. It is a key step in the analysis of DInSAR. The classical phase unwrapping methods are either of path following type or of minimum-norm type. However, if the coherence of the two images is very low, the both methods will get error result. In application of CRDInSAR, due to the scattered points, the phase unwrapping of corner reflectors is only dealt with on a sparse grid, so all the reflectors are connected with Delaunay triangulation firstly, which can be used to define neighboring points and elementary cycles. When the monitoring ground deformation is slow, that is unwrapped neighboring-CR phase gradients are supposed to equal their wrapped-phase counterparts, then path-following method and Phase unwrapping using Coefficient of Elevation-Phase-Relation can be used to phase unwrapping. However, in the cases of unwrapped gradients exceeding one-half cycle, minimum cost flow (MCF) method can be used to unwrap the interferogram.

Paper Details

Date Published: 8 August 2007
PDF: 8 pages
Proc. SPIE 6752, Geoinformatics 2007: Remotely Sensed Data and Information, 67520Q (8 August 2007); doi: 10.1117/12.760459
Show Author Affiliations
Wenxue Fu, Nanjing Univ. (China)
Xiaofang Guo, China Aero Geophysical Survey & Remote Sensing Ctr. for Land and Resources (China)
Qingjiu Tian, Nanjing Univ. (China)


Published in SPIE Proceedings Vol. 6752:
Geoinformatics 2007: Remotely Sensed Data and Information

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