Ephrem, Teshale (PhD)Mequanent, Mulugeta (Mr.) Co-AdviserTewodros, Mulugeta2019-04-102023-11-282019-04-102023-11-282019-01http://etd.aau.edu.et/handle/12345678/17770Asphalt pavement is one of the most dominant infrastructure consuming huge investment and play as a blood vessel to a nation. The surface layer of asphalt pavement is a multilayer structure. It commonly has three sub-layers: the top surface layer (Asphalt), the intermediate surface layer (Base course) and the following surface layer (Sub base). The thicknesses of the surface layer and the top surface layer have great importance on quality condition and maintenance of asphalt pavements. Estimating asphalt pavement layer thicknesses and material type accurately helps to evaluate the pavement condition. Common methods of estimation of these parameters includes boring a hole (coring) at selected sampling points, used to estimate the asphalt layer thicknesses and material characterization, have limitations. Ground Penetrating Radar (GPR) represents an alternative non-destructive approach which alleviates some of this limitation. GPR signal processing is a non-destructive technique, particularly promising for pavement characteristics interpretation. The accuracy of asphalt pavement layer thicknesses estimation and material characterization depends on GPR data analysis employing different estimation approaches and based on the incoming signal from the radar. The focus of the thesis is to investigate asphalt pavement thickness and material characterization using GPR data. Finite Difference Time Domain (FDTD) simulation and GPRmax are tools used to validate the research. This has to be taken seriously.en-USGPRMatching FilterDielectric ConstantsAsphalt Pavement Layer ThicknessThesis