Ground-Penetrating Radar Antenna Design for Homogeneous and Low-Loss Dielectric Multilayer Media

Ground-Penetrating Radar Antenna Modeling

-Detecting subsurface objects by using GroundPenetrating Radar (GPR) has received considerable interest in recent years. In order to interpret radar signals from buried objects, one must have the ability to model a large range of objects, grounds and radar antennas, theoretically or numerically, so that a real GPR system can be simulated. Many investigations have been done for modeling objects ...

Design of a Reconfigurable Antenna for Ground Penetrating Radar Applications

This paper deals with the design and numerical analysis of a reconfigurable antenna implemented according to the total geometry morphing approach. The reconfigurable antenna is designed so to resemble a reference bowtie antenna, suitable for a stepped frequency Ground Penetrating Radar (GPR) applications, with geometry variable in order to work in different operative conditions. In particular, ...

Ground Penetrating Radar Survey Design

Characterisation of a ground penetrating radar antenna in lossless homogeneous and lossy heterogeneous environments

Directly measuring the radiation characteristics of Ground Penetrating Radar (GPR) antennas in environments typically encountered in GPR surveys, presents many practical difficulties. However it is very important to understand how energy is being transmitted and received by the antenna, especially for areas of research such as antenna design, signal processing, and inversion methodologies. To o...

Ground Penetrating Radar Image Preprocessing for Embedded Object in Media

The detection of embedded object from ground penetrating radar GPR imagery is our goal. The GPR image is a cross sectional slices. The embedded objects are metal and/or plastic type. This research has many real world applications such as remote sensing, geology, medicine and civil. The proposed method starts with two dimensional 2D image preprocessing for each slice. The preprocessing involves ...