Asphalt pavement is one of the most dominant infrastructure consuming hugerninvestment and play as a blood vessel to a nation. The surface layer of asphaltrnpavement is a multilayer structure. It commonly has three sub-layers: the top surfacernlayer (Asphalt), the intermediate surface layer (Base course) and the followingrnsurface layer (Sub base). The thicknesses of the surface layer and the top surfacernlayer have great importance on quality condition and maintenance of asphalt pavements.rnEstimating asphalt pavement layer thicknesses and material type accurately helpsrnto evaluate the pavement condition. Common methods of estimation of thesernparameters includes boring a hole (coring) at selected sampling points, used tornestimate the asphalt layer thicknesses and material characterization, have limitations.rnGround Penetrating Radar (GPR) represents an alternative non-destructivernapproach which alleviates some of this limitation.rnGPR signal processing is a non-destructive technique, particularly promising forrnpavement characteristics interpretation. The accuracy of asphalt pavement layerrnthicknesses estimation and material characterization depends on GPR data analysisrnemploying different estimation approaches and based on the incoming signalrnfrom the radar. The focus of the thesis is to investigate asphalt pavement thicknessrnand material characterization using GPR data. Finite Difference Time Domainrn(FDTD) simulation and GPRmax are tools used to validate the research. Thisrnhas to be taken seriously.