TY - JOUR
T1 - High-Resolution Velocity Analysis Method Using the ℓ-1 Norm Regularized Least-Squares Method for Pavement Inspection
AU - Yi, Li
AU - Zou, Lilong
AU - Takahashi, Kazunori
AU - Sato, Motoyuki
N1 - Funding Information:
Manuscript received February 19, 2017; revised September 21, 2017; accepted December 22, 2017. Date of publication January 25, 2018; date of current version March 9, 2018. This work was supported in part by Council for Science, Technology and Innovation, “Cross-ministerial Strategic Innovation Promotion Program, Infrastructure Maintenance, Renovation, and Management,” (funding agency: NEDO), in part by the JSPS Grant-in-Aid for Scientific Research (A) 26249058, in part by the scheme of Human Resource Development Program in Renewable Energy Department for the project of enhancing the function of Fukushima Renewable Energy Institute, and in part by the National Institute of Advanced Industrial Science and Technology. (Corresponding author: Li Yi.) L. Yi is with the National institute of Advanced Industrial Science and Technology, Koriyama, 963-0298 Japan (e-mail: li.yi@aist.go.jp).
Publisher Copyright:
© 2008-2012 IEEE.
PY - 2018/3
Y1 - 2018/3
N2 - We propose a high-resolution velocity analysis method to estimate the electromagnetic wave propagation velocity in subsurface medium. The estimation is achieved by applying the ℓ-1 norm regularized least-squares method to the conventional common-midpoint (CMP) velocity analysis algorithm. The proposed method can provide not only higher resolution than the conventional velocity analysis method, but can also be applied with a coarse sampling array system, such as our array ground penetrating radar YAKUMO, which returns eight CMP traces within a two meter width. The main purpose of this approach is for precise pavement inspection at shallow depths. We applied this method to both a simulated dataset and real data acquired by YAKUMO at a model airport taxiway to detect the slight velocity changes caused by millimeter-thin cracks filled with air or water within the 15 cm-thick asphalt pavement. In both cases slight velocity changes of about 0.005 m/ns can be detected, and the difference between air- and water-filled cracks can be distinguished. Also, this method is applied to a data acquired at airport taxi-way, the damaged parts are detected successfully and shows good agreement with the corning results. The results indicate that the proposed method is effective for pavement inspection, especially in the presence of thin cracks that cannot be seen directly with the reflected signal.
AB - We propose a high-resolution velocity analysis method to estimate the electromagnetic wave propagation velocity in subsurface medium. The estimation is achieved by applying the ℓ-1 norm regularized least-squares method to the conventional common-midpoint (CMP) velocity analysis algorithm. The proposed method can provide not only higher resolution than the conventional velocity analysis method, but can also be applied with a coarse sampling array system, such as our array ground penetrating radar YAKUMO, which returns eight CMP traces within a two meter width. The main purpose of this approach is for precise pavement inspection at shallow depths. We applied this method to both a simulated dataset and real data acquired by YAKUMO at a model airport taxiway to detect the slight velocity changes caused by millimeter-thin cracks filled with air or water within the 15 cm-thick asphalt pavement. In both cases slight velocity changes of about 0.005 m/ns can be detected, and the difference between air- and water-filled cracks can be distinguished. Also, this method is applied to a data acquired at airport taxi-way, the damaged parts are detected successfully and shows good agreement with the corning results. The results indicate that the proposed method is effective for pavement inspection, especially in the presence of thin cracks that cannot be seen directly with the reflected signal.
KW - Ground penetrating radar (GPR)
KW - inspection
KW - least-squares methods
KW - sparse array antennas
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U2 - 10.1109/JSTARS.2018.2791970
DO - 10.1109/JSTARS.2018.2791970
M3 - Article
AN - SCOPUS:85041352491
VL - 11
SP - 1005
EP - 1015
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
SN - 1939-1404
IS - 3
ER -