Correctly locating the tunnel lining cavity is extremely important tunnel quality inspection.High-accuracy imaging results are hard to obtain because conventional one-way wave migration is greatly aff ected by lateral...Correctly locating the tunnel lining cavity is extremely important tunnel quality inspection.High-accuracy imaging results are hard to obtain because conventional one-way wave migration is greatly aff ected by lateral velocity change and inclination limitation and because the diff racted wave cannot be accurately returned to the real spatial position of the lining cavity.This paper presents a tunnel lining cavity imaging method based on the groundpenetrating radar(GPR)reverse-time migration(RTM)algorithm.The principle of GPR RTM is described in detail using the electromagnetic wave equation.The finite-difference timedomain method is employed to calculate the backward extrapolation electromagnetic fi elds,and the zero-time imaging condition based on the exploding-reflector concept is used to obtain the RTM results.On this basis,the GPR RTM program is compiled and applied to the simulated and observed GPR data of a typical tunnel lining cavity GPR model and a physical lining cavity model.Comparison of RTM and Kirchhoff migration results reveals that the RTM can better converge the diff racted waves of steel bar and cavity to their true position and have higher resolution and better suppress the eff ect of multiple interference and clutter scattering waves.In addition,comparison of RTM results of diff erent degrees of noise shows that RTM has strong anti-interference ability and can be used for the accurate interpretation of radar profi le in a strong interference environment.展开更多
The reverse time migration(RTM)of ground penetrating radar(GPR)is usually implemented in its two-dimensional(2D)form,due to huge computational cost.However,2D RTM algorithm is difficult to focus the scattering signal ...The reverse time migration(RTM)of ground penetrating radar(GPR)is usually implemented in its two-dimensional(2D)form,due to huge computational cost.However,2D RTM algorithm is difficult to focus the scattering signal and produce a high precision subsurface image when the object is buried in a complicated subsurface environment.To better handle the multi-off set GPR data,we propose a three-dimensional(3D)prestack RTM algorithm.The high-order fi nite diff erence time domian(FDTD)method,with the accuracy of eighth-order in space and second-order in time,is applied to simulate the forward and backward extrapolation electromagnetic fi elds.In addition,we use the normalized correlation imaging condition to obtain pre-stack RTM result and the Laplace fi lter to suppress the low frequency noise generated during the correlation process.The numerical test of 3D simulated GPR data demonstrated that 3D RTM image shows excellent coincidence with the true model.Compared with 2D RTM image,the 3D RTM image can more clearly and accurately refl ect the 3D spatial distribution of the target,and the resolution of the imaging results is far better.Furthermore,the application of observed GPR data further validates the eff ectiveness of the proposed 3D GPR RTM algorithm,and its fi nal image can more reliably guide the subsequent interpretation.展开更多
基金supported by the National Natural Science Foundation of China (Nos. 41764005, 41604039, 41604102, and 41574078)Guangxi Natural Science Foundation of China (Nos. 2016GXNSFBA380082 and 2016GXNSFBA380215)+2 种基金Guangxi Young and Middle-aged Teacher Basic Ability Improvement Project (No. KY2016YB199)Guangxi Collaborative Innovation Center for Exploration of Hidden Nonferrous Metal Deposits and Development of New Materials Project (No. GXYSXTZX2017-II-5)Guangxi Scholarship Fund of Guangxi Education Department。
文摘Correctly locating the tunnel lining cavity is extremely important tunnel quality inspection.High-accuracy imaging results are hard to obtain because conventional one-way wave migration is greatly aff ected by lateral velocity change and inclination limitation and because the diff racted wave cannot be accurately returned to the real spatial position of the lining cavity.This paper presents a tunnel lining cavity imaging method based on the groundpenetrating radar(GPR)reverse-time migration(RTM)algorithm.The principle of GPR RTM is described in detail using the electromagnetic wave equation.The finite-difference timedomain method is employed to calculate the backward extrapolation electromagnetic fi elds,and the zero-time imaging condition based on the exploding-reflector concept is used to obtain the RTM results.On this basis,the GPR RTM program is compiled and applied to the simulated and observed GPR data of a typical tunnel lining cavity GPR model and a physical lining cavity model.Comparison of RTM and Kirchhoff migration results reveals that the RTM can better converge the diff racted waves of steel bar and cavity to their true position and have higher resolution and better suppress the eff ect of multiple interference and clutter scattering waves.In addition,comparison of RTM results of diff erent degrees of noise shows that RTM has strong anti-interference ability and can be used for the accurate interpretation of radar profi le in a strong interference environment.
基金This work is supported by the National Natural Science Foundation of China(No.41604039,41604102,41764005,41574078)Guangxi Natural Science Foundation project(No.2020GXNSFAA159121,2016GXNSFBA380215).
文摘The reverse time migration(RTM)of ground penetrating radar(GPR)is usually implemented in its two-dimensional(2D)form,due to huge computational cost.However,2D RTM algorithm is difficult to focus the scattering signal and produce a high precision subsurface image when the object is buried in a complicated subsurface environment.To better handle the multi-off set GPR data,we propose a three-dimensional(3D)prestack RTM algorithm.The high-order fi nite diff erence time domian(FDTD)method,with the accuracy of eighth-order in space and second-order in time,is applied to simulate the forward and backward extrapolation electromagnetic fi elds.In addition,we use the normalized correlation imaging condition to obtain pre-stack RTM result and the Laplace fi lter to suppress the low frequency noise generated during the correlation process.The numerical test of 3D simulated GPR data demonstrated that 3D RTM image shows excellent coincidence with the true model.Compared with 2D RTM image,the 3D RTM image can more clearly and accurately refl ect the 3D spatial distribution of the target,and the resolution of the imaging results is far better.Furthermore,the application of observed GPR data further validates the eff ectiveness of the proposed 3D GPR RTM algorithm,and its fi nal image can more reliably guide the subsequent interpretation.
