Ground penetrating radar (GPR) technology has been widely used in pavement assessment over the last decade. Assessing the subgrade condition and monitoring its temporal variation provide valuable information regarding changes associated with pavement deterioration, allowing for the beneficial prediction of future road maintenance. This paper presents a method to estimate the density and water content of prepared subgrade soils of highly plastic silt using a 2 GHz GPR scan system and a simple exponential model. A bulk density prediction model was developed based on electromagnetic mixing theory to back calculate subgrade soils density. The model developed determines the soil’s dielectric constant, considering dielectric and volumetric properties of the three major components of soil: air, water, and solid particles. A series of laboratory tests was conducted on six (6) soil samples at various density levels to validate the newly developed model. For validation purposes, sand cone and dynamic cone penetration (DCP) tests were performed and compared with the estimated soils strength from GPR data. The results show that the prediction of soils density and stiffness using nondestructive technology helps efficiently forecast not only pavement deterioration, but potential risks to the subsurface pavement structure with all the advances of time saving using air coupled GPR antenna mounted on a moving vehicle.
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