Detecting and Classifying UXO

This article presents state-of-the-art unexploded ordnance detection and classification, including examples from recent field-demonstration studies. After reviewing sensor technologies, with a focus on magnetic and electromagnetic systems, the authors discuss advanced processing techniques that allow for reliable discrimination between hazardous ordnance and harmless metallic clutter. Finally, the article shows results from a large-scale field demonstration conducted in 2011. In this case study, electromagnetic data acquired with an advanced sensor is used to identify ordnance at the site, reducing the number of excavations required with conventional metal detectors by 85%

Geophysical investigation of the Pb-Zn deposit of Lontzen-Poppelsberg, Belgium

The drillhole information from the Lontzen-Poppelsberg site has demonstrated three orebodies and has allowed the estimation of the extension of the lodes, their dip, and the location at the ground surface. The localisation of the lodes makes them excellent targets for further exploration with geophysics. This deposit is classified as a Mississippi Valley Type (MVT) deposit. It consists mainly of Pb-Zn-Fe sulphides that display contrasting values in resistivity, chargeability, density, and magnetic susceptibility, with regards to the sedimentary host rocks. The dipole-dipole direct current (DC) resistivity and induce polarization (IP) profiles have been collected and inverted to successfully delineate the Pb-Zn mineralization and the geological structures. Short-spacing EM34 electromagnetic conductivity data were collected mainly on the top of Poppelsberg East lode and have revealed a conductive body matching with the geologically modelled mineralization. Gravity profiles have been carried out perpendicularly to the lode orientation; they show a strong structural anomaly. High resolution ground magnetic data were collected over the study area, but they showed no anomaly over the ore deposits. The geophysical inversion results are complementary to the model based on drill information, and allow us to refine the delineation of the mineralization. The identification of the geophysical signatures of this deposit permits targeting new possible mineralization in the area

Catholic Relief Services Develops MRE Materials

This article presents state-of-the-art unexploded ordnance detection and classification, including examples from recent field-demonstration studies. After reviewing sensor technologies, with a focus on magnetic and electromagnetic systems, the authors discuss advanced processing techniques that allow for reliable discrimination between hazardous ordnance and harmless metallic clutter. Finally, the article shows results from a large-scale field demonstration conducted in 2011. In this case study, electromagnetic data acquired with an advanced sensor is used to identify ordnance at the site, reducing the number of excavations required with conventional metal detectors by 85%

Multi-function intelligent robotic in metals detection applications

Recent technologies for robotics have been offered an effective and efficient solution to safeguard workers from risks in their work environments. These risks involve radioactive, toxic, explosive and mines. In this paper, design and implement computer robot based on metal detection as well as avoiding obstacles automatically. The proposed wireless controlled robotic vehicle can be used in metal detection applications such as landmine detection, obstacles avoidance, selecting best routing without imposing human's harms and workforce aspects. The robotic wheel can sense the obstacles that positioning at ahead of its path, and also avoids the obstacles forward, left and right of its routes. The robot is controlled by using Bluetooth wireless communication to interface between the controller and the implemented robot. Furthermore, sensor IR (FC-03) for the metal detector and used ultrasonic sensor (HC-SR04) for objects or obstacles sensing. The presented controlled robotic designed for desert and dry soil that can replace the human role in avoiding obstacles and metal detection capabilities. The produced robot was useful due to it can detect metals and avoiding obstacles consecutively besides it was effective to select the best route based on the intelligent technique that adopted, the predefined metals by using an intelligent decision maker for route finder in a flat surface environment

A Multidisciplinary Analysis of Frequency Domain Metal Detectors for Humanitarian Demining

This thesis details an analysis of metal detectors (low frequency electromagnetic induction devices) with emphasis on Frequency Domain (FD) systems and the operational conditions of interest to humanitarian demining. After an initial look at humanitarian demining and a review of their basic principles we turn our attention to electromagnetic induction modelling and to analytical solutions to some basic FD direct (forward) problems. The second half of the thesis focuses then on the analysis of an extensive amount of experimental data. The possibility of target classification is first discussed on a qualitative basis, then quantitatively. Finally, we discuss shape and size determination via near field imaging

Ground‐Penetrating Radar for Close‐in Mine Detection

In this chapter, two of the major challenges in the application of ground‐penetrating radar in humanitarian demining operations are addressed: (i) development and testing of affordable and practical ground penetrating radar (GPR)‐based systems, which can be used off‐ground and (ii) development of robust signal processing techniques for landmines detection and identification. Different approaches developed at the Royal Military Academy in order to demonstrate the possibility of enhancing close‐range landmine detection and identification using ground‐penetrating radar under laboratory and outdoor conditions are summarized here. Data acquired using different affordable and practical GPR‐based systems are used to validate a number of promising developments in signal processing techniques for target detection and identification. The proposed approaches have been validated with success in laboratory and outdoor conditions and for different scenarios, including antipersonnel, low‐metal content landmines, improvised explosive devices and real mine‐affected soils