Reference : Split-Band Interferometry-Assisted Phase Unwrapping for the Phase Ambiguities Correction
Scientific journals : Article
Physical, chemical, mathematical & earth Sciences : Earth sciences & physical geography
Split-Band Interferometry-Assisted Phase Unwrapping for the Phase Ambiguities Correction
Libert, Ludivine mailto [Université de Liège > > CSL (Centre Spatial de Liège) >]
De Rauw, Dominique mailto [Université de Liège > > CSL (Centre Spatial de Liège) >]
d'Oreye, Nicolas mailto [> >]
Barbier, Christian mailto [Université de Liège > > CSL (Centre Spatial de Liège) >]
Orban, Anne mailto [Université de Liège > > CSL (Centre Spatial de Liège) >]
Remote Sensing
Advances in SAR: Sensors, Methodologies, and Applications
[en] Synthetic Aperture Radar ; Interferometry ; phase unwrapping ; split-band ; multichromatic analysis
[en] Split-Band Interferometry (SBInSAR) exploits the large range bandwidth of the new generation of synthetic aperture radar (SAR) sensors to process images at subrange bandwidth. Its application to an interferometric pair leads to several lower resolution interferograms of the same scene with slightly shifted central frequencies. When SBInSAR is applied to frequency-persistent scatterers, the linear trend of the phase through the stack of interferograms can be used to perform absolute and spatially independent phase unwrapping. While the height computation has been the main concern of studies on SBInSAR so far, we propose instead to use it to assist conventional phase unwrapping. During phase unwrapping, phase ambiguities are introduced when parts of the interferogram are separately unwrapped. The proposed method reduces the phase ambiguities so that the phase can be connected between separately unwrapped regions. The approach is tested on a pair of TerraSAR-X spotlight images of Copahue volcano, Argentina. In this framework, we propose two new criteria for the frequency-persistent scatterers detection, based respectively on the standard deviation of the slope of the linear regression and on the phase variance stability, and we compare them to the multifrequency phase error. Both new criteria appear to be more suited to our approach than the multifrequency phase error. We validate the SBInSAR-assisted phase unwrapping method by artificially splitting a continuous phase region into disconnected subzones. Despite the decorrelation and the steep topography affecting the volcanic test region, the expected phase ambiguities are successfully recovered whatever the chosen criterion to detect the frequency-persistent scatterers. Comparing the aspect ratio of the distributions of the computed phase ambiguities, the analysis shows that the phase variance stability is the most efficient criterion to select stable targets and the slope standard deviation gives satisfactory results.
Centre Spatial de Liège
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