TY - JOUR
T1 - Atmospheric Phase Compensation in Extreme Weather Conditions for Ground-Based SAR
AU - Karunathilake, Amila
AU - Sato, Motoyuki
N1 - Funding Information:
Manuscript received May 31, 2019; revised October 18, 2019, December 12, 2019, January 29, 2020, and May 21, 2020; accepted June 18, 2020. Date of publication June 23, 2020; date of current version July 8, 2020. This work was supported in part by JSPS Grant-in-Aid for Scientific Research (A) under Grant 26249058 and in part by Tohoku University-NICT Joint Matching Project. (Corresponding author: Amila Karunathilake.) Amila Karunathilake is with the Advanced Technologies Research Laboratory, Asia Air Survey Company, Ltd., Kawasaki 215-0004, Japan (e-mail: dr.amilatk@gmail.com).
Publisher Copyright:
© 2008-2012 IEEE.
PY - 2020
Y1 - 2020
N2 - Herein, a semiempirical model is proposed to remove the atmospheric phase screen (APS) that occurs during ground-based synthetic aperture radar (GB-SAR) monitoring in steep mountainous areas with extreme weather conditions. The proposed method is based on a model-based statistical technique, which combines the topographical information and the estimated phase of interferograms. A 3-D geographical model was designed to investigate the effect of topographical irregularities, such as elevation, slope, and their correlation with the APS. The observed phases were then modeled according to the altitude and range of the 3-D topographical structure seen by the radar. A two-stage semiempirical algorithm is proposed to compensate for the APS in the spatial domain. Herein, the temporal changes in meteorological parameters, such as the atmospheric temperature, pressure, or humidity, were not considered for phase correction, drastically reducing the model background information and providing faster data processing for real-time GB-SAR monitoring. The proposed model was applied to the mountainous environment of a road reconstruction site in Minami-Aso, Kumamoto, Japan, where large-scale landslides were triggered after the Kumamoto earthquake in April 2016.
AB - Herein, a semiempirical model is proposed to remove the atmospheric phase screen (APS) that occurs during ground-based synthetic aperture radar (GB-SAR) monitoring in steep mountainous areas with extreme weather conditions. The proposed method is based on a model-based statistical technique, which combines the topographical information and the estimated phase of interferograms. A 3-D geographical model was designed to investigate the effect of topographical irregularities, such as elevation, slope, and their correlation with the APS. The observed phases were then modeled according to the altitude and range of the 3-D topographical structure seen by the radar. A two-stage semiempirical algorithm is proposed to compensate for the APS in the spatial domain. Herein, the temporal changes in meteorological parameters, such as the atmospheric temperature, pressure, or humidity, were not considered for phase correction, drastically reducing the model background information and providing faster data processing for real-time GB-SAR monitoring. The proposed model was applied to the mountainous environment of a road reconstruction site in Minami-Aso, Kumamoto, Japan, where large-scale landslides were triggered after the Kumamoto earthquake in April 2016.
KW - Displacement measurement
KW - interferometry
KW - radar
KW - remote sensing
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U2 - 10.1109/JSTARS.2020.3004341
DO - 10.1109/JSTARS.2020.3004341
M3 - Article
AN - SCOPUS:85089183516
SN - 1939-1404
VL - 13
SP - 3806
EP - 3815
JO - IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
JF - IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
M1 - 9123595
ER -