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Anisotropic Phase Unwrapping for Synthetic Aperture Radar Interferometry

Danudirdjo D.a,b, Hirose A.a

a Department of Electrical Engineering and Information Systems, University of Tokyo, Tokyo, Japan
b School of Electrical Engineering and Informatics, Bandung Institute of Technology, Bandung, 40132, India

[vc_row][vc_column][vc_row_inner][vc_column_inner][vc_separator css=”.vc_custom_1624529070653{padding-top: 30px !important;padding-bottom: 30px !important;}”][/vc_column_inner][/vc_row_inner][vc_row_inner layout=”boxed”][vc_column_inner width=”3/4″ css=”.vc_custom_1624695412187{border-right-width: 1px !important;border-right-color: #dddddd !important;border-right-style: solid !important;border-radius: 1px !important;}”][vc_empty_space][megatron_heading title=”Abstract” size=”size-sm” text_align=”text-left”][vc_column_text]© 1980-2012 IEEE.This paper presents a new phase unwrapping method for synthetic aperture radar interferometry (InSAR). Compared with other phase observations, InSAR data are unique due to the foreshortening effect in SAR images. This effect makes the interferogram phase anisotropic, i.e., the statistics of phase gradients along the ground-range axis are different from those in the azimuth direction. Furthermore, the distribution of phase gradients in the ground-range direction is not symmetric. The proposed method targets the most likely unwrapped phase by considering the foreshortening effect in SAR observation, noise characteristics in InSAR phase data, and fractional Brownian surface as a suitable model for natural topography. Experiments with simulated terrains and real InSAR data show that the method gives comparable or better digital elevation model results than the other tested methods.[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Author keywords” size=”size-sm” text_align=”text-left”][vc_column_text]Anisotropic phase,Azimuth direction,Digital elevation model,Noise characteristic,Phase observations,Phase unwrapping,Phase unwrapping methods,Synthetic aperture radar interferometry[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Indexed keywords” size=”size-sm” text_align=”text-left”][vc_column_text]Digital elevation model (DEM),fractals,phase unwrapping,synthetic aperture radar (SAR)[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Funding details” size=”size-sm” text_align=”text-left”][vc_column_text][/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”DOI” size=”size-sm” text_align=”text-left”][vc_column_text]https://doi.org/10.1109/TGRS.2015.2391191[/vc_column_text][/vc_column_inner][vc_column_inner width=”1/4″][vc_column_text]Widget Plumx[/vc_column_text][/vc_column_inner][/vc_row_inner][/vc_column][/vc_row][vc_row][vc_column][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][/vc_column][/vc_row]