The Fdtd Modeling And Simulation Of Gpr

GPR is a new type of electromagnetic waves detection technology, which with quick, light, no damage, low-cost, high-resolution features and so on. It is widely used in traffic infrastructure, urbanistic infrastructure, military and archaeological area. Currently, in fact engineering application, there are some problems in GPR method:(1) Its interpretation of radar images is relatively low degree of automation, and to a large extent it is affected by human factors; (2)The staffs need many fact engineering experience to acquire some experience. By analyzing all kinds of pavement structure model's forward model results, and taking examples from exploration technology to process and interpret the data, we can accumulate the experience according to the GPR's image discrimination of underground structures. We can improve the accuracy of interpretation by using GPR method.After 40 years development of FDTD method, it has become a mature numerical method for electromagnetic, its calculation accuracy is very precise. This thesis will carry on the modeling and simulation of highway infrastructure under the method of FDTD, and deal with the simulation results, and enforce 3D visualization display of the 3D results.The main research outcome and conclusions are as follows:1) Based on MATLAB, programming FDTD GPR one-dimensional simulation.2) Establishing 2D-FDTD forward model of the pavement structure which contains such target body as steel, hollow and so on, by using the software GprMax2D.3) Establishing 2D-FDTD forward model of the bridge deck which contains such target body as steel, hollow and so on, by using the software GprMax2D.The results show that the typical shape of the obstacle from the numerical modeling of images through pursuing the forward simulation by using the software GprMax2D can clearly reflect the characteristics of their respective imaging. And they provide a basis for the establishment of image database of objects of the typical shapes, and provide a basis and experience for complex image recognition of Ground Penetrating Radar in the future.