TY - JOUR
T1 - Hybrid Polarimetric GPR Calibration and Elongated Object Orientation Estimation
AU - Liu, Hai
AU - Huang, Xiaoyun
AU - Han, Feng
AU - Cui, Jie
AU - Spencer, Billie F.
AU - Xie, Xiongyao
N1 - Funding Information:
Manuscript received September 15, 2018; revised January 17, 2019 and March 10, 2019; accepted April 5, 2019. Date of publication May 19, 2019; date of current version July 30, 2019. This work was supported in part by the National Key Research and Development Program of China under Grant 2016YFC0800200, and in part by the National Natural Science Foundation of China under Grants 41874120 and 41504111. (Corresponding authors: Jie Cui and Xiongyao Xie.) H. Liu is with the School of Civil Engineering, Guangzhou University, Guangzhou 510006, China (e-mail: hliu@gzhu.edu.cn).
Publisher Copyright:
© 2008-2012 IEEE.
PY - 2019/7
Y1 - 2019/7
N2 - Ground penetrating radar (GPR) has been widely applied to the detection of subsurface elongated targets, such as underground pipes, concrete rebars, and subsurface fractures. The orientation angle of a subsurface elongated target can hardly be delineated by a commercial single-polarization GPR system. In this paper, a hybrid dual-polarimetric GPR system, which consists of a circularly polarized transmitting antenna and two linearly polarized receiving antenna, is employed to detect buried elongated objects. A polarimetric calibration experiment using a gridded trihedral is carried out to correct the imbalances and cross talk between the two receiving channels. A full-polarimetric scattering matrix is extracted from the double-channel GPR signals reflected from a buried elongated object. An improved Alford rotation method is proposed to estimate the orientation angle of the elongated object from the extracted scattering matrix, and its accuracy is validated by a numerical test. A laboratory experiment was further conducted to detect five metal rebar buried in dry sand at different orientation angle relative to the GPR scan direction. The maximum relative error of the estimated angles of the buried rebars in the migrated GPR images is less than 5%. It is concluded that radar polarimetry can provide not only richer information than single-polarization GPR, but also a reliable approach for orientation estimation of a subsurface elongated object.
AB - Ground penetrating radar (GPR) has been widely applied to the detection of subsurface elongated targets, such as underground pipes, concrete rebars, and subsurface fractures. The orientation angle of a subsurface elongated target can hardly be delineated by a commercial single-polarization GPR system. In this paper, a hybrid dual-polarimetric GPR system, which consists of a circularly polarized transmitting antenna and two linearly polarized receiving antenna, is employed to detect buried elongated objects. A polarimetric calibration experiment using a gridded trihedral is carried out to correct the imbalances and cross talk between the two receiving channels. A full-polarimetric scattering matrix is extracted from the double-channel GPR signals reflected from a buried elongated object. An improved Alford rotation method is proposed to estimate the orientation angle of the elongated object from the extracted scattering matrix, and its accuracy is validated by a numerical test. A laboratory experiment was further conducted to detect five metal rebar buried in dry sand at different orientation angle relative to the GPR scan direction. The maximum relative error of the estimated angles of the buried rebars in the migrated GPR images is less than 5%. It is concluded that radar polarimetry can provide not only richer information than single-polarization GPR, but also a reliable approach for orientation estimation of a subsurface elongated object.
KW - Azimuth estimation
KW - ground penetrating radar (GPR)
KW - hybrid polarization
KW - subsurface elongated target
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U2 - 10.1109/JSTARS.2019.2912339
DO - 10.1109/JSTARS.2019.2912339
M3 - Article
AN - SCOPUS:85070454869
SN - 1939-1404
VL - 12
SP - 2080
EP - 2087
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
IS - 7
M1 - 8718348
ER -