The design and subsequent testing of suitable antennas and of complete ground-penetrating radar (GPR) systems can be both time consuming and expensive, with the need to understand the performance of a system in realistic environments of great importance to the end user. Through the use of suitably validated simulations, these costs could be significantly reduced, allowing an economical capability to be built which can accurately predict the performance of novel GPR antennas and existing commercial-off-the-shelf (COTS) systems in a user defined environment. This paper focuses on a preliminary validation of the open source software gprMax<sup>1</sup> which features the ability to custom define antennas, targets, clutter objects and realistic heterogeneous soils. As an initial step in the assessment of the software, a comparison of the modelled response of targets buried in sand to experimental data has been undertaken, with the variation in response with antenna stand-off height investigated. This was conducted for both a simple bespoke bow-tie antenna design as well as for a Geophysical Survey Systems, Inc. (GSSI) commercial system,<sup>2</sup> building upon previous work<sup>3</sup> which explored the fidelity of gprMax in reproducing the S11 of simple antenna designs.
This paper presents and compares two established methods for the automatic detection of landmines in ground penetrating radar (GPR) data. B-scan data of standard GPR targets and simulant landmines were collected from indoor sand and soil lanes. The images were pre-processed and the least squares method and the Hough transform were applied to objects of interest for the detection of hyperbolic signatures in the data. One drawback of the Hough transform is that it can be computationally expensive as it requires a search in 4-D space for hyperbolic shapes. In this case, it has been simplified so only a search in 1-D space is required, however this simplification did result in some missed detections.
Conventional metal detectors are established and trusted tools for landmine detection, but their inability to precisely locate a target and discriminate mines from clutter leads to a high false alarm rate and slow rate of progress. This paper reports on developments to the Marmot advanced metal detector, which uses an array of coils to precisely locate a metal target in three dimensions and identify it. Recent developments allow the detector to calculate the magnetic polarizability tensor of a metal object. The magnetic polarizability tensor is unique to a particular target, and is a property of the metal's shape, size, conductivity, permeability and orientation. The eigenvalues of the magnetic polarizability tensor are compared to a library of values in the detector's software, representing common types of mine and clutter. In this way, Marmot can often quickly identify a detected object as a type of mine or a piece of clutter. This identification is independent of the target's orientation and, within limits, its position relative to the search head, thus providing the potential for a target recognition facility.
This paper presents the results of tests to determine Marmot's ability to detect, precisely locate and identify common landmines. Tests have been conducted in air and in several types of soil. The instrument is a first step in developing the concept for landmine clearance. Issues for further investigation have been identified, including use of the instrument for identifying high metal content landmines, application of the soil rejection function and signal to noise issues.