In this paper, an object characterization method based on neural networks is developed for GPR subsurface imaging. Currently, most existing studies demonstrate detecting and imaging objects of cylindrical shapes. While in this paper, no restriction is imposed on the object shape. Three neural network algorithms are exploited to characterize different types of object signatures, including object...

This paper addresses the problem of inverting Ground Penetrating Radar (GPR) data, to find the buried inclusions characteristics depth and radii considering a nonhomogenous host media by using neural networks (NN). The aim is the detection and characterization of inclusions in concrete structures. A novel asynchronous model is proposed to the NN arrangement. The model is shown to outperform the...

Ground penetrating Radar (GPR) is an interesting device that can allow a non-destructive auscultation of the underground without any excavation. It is based on the use of high frequency electromagnetic waves, including reflection or diffraction that allows the detection of buried objects. In this work, we studied the possibility of using GPR for detecting of human targets under the rubble cause...

<abstract> <p>This study analyses the façades of a white concrete building located in Cádiz (Spain). Numerous sections cladding on have become detached and there are clear signs reinforcement corrosion. For purposes this study, arrangement was evaluated by georadar (GPR). Cylindrical cores measuring 10 cm diameter 15–18 depth were extracted their carbonation front evaluated. Samples...

Ground penetrating radar (GPR) is a non-destructive geophysical method that uses electromagnetic waves to image the subsurface. A typical GPR system has three main components: transmitter and receiver, directly connected to the transmitting and receiving antennas, and a control unit. Electromagnetic pulses are transmitted into the subsurface and the earth response is recorded. The GPR method is...