1,893 research outputs found

    A Survey of Research on Sensor Technology for Landmine Detection

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    According to official figures, more than 100 million landmines lie buried around the world. Although intended for warfare, these mines remain active after warfare ends. Each day these mines are triggered accidentally by civilian activities, ravaging the land and killing or maiming innocent people. To help stop this destruction of the environment and humanity, the scientific community must develop effective humanitarian demining. Mine detection is especially vital to humanitarian demining. The goal of military demining is to clear enough mines quickly to allow troops through a land area. Military demining usually requires mine destruction rates of 80%. The goal of humanitarian demining, in contrast, is to clear enough mines to permit normal civilian use of the land (e.g., construction or agriculture). Humanitarian demining thus demands a destruction rate approaching perfection: UN specifications require a rate better than 99.6%. Of course, a critical aspect of mine clearance is mine detection. Before one can remove mines, one must locate them. To aid scientific inquiry into mine detection, this paper reviews the major current and developing technologies for mine detection. We do not claim to include every technology. Often the details of research intended for specific military applications are difficult to attain. This paper highlights significant studies of mine detection technologies, discussed in several recent conferences and in many recent articles and reports, to show promising directions for future research

    A Multidisciplinary Analysis of Frequency Domain Metal Detectors for Humanitarian Demining

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    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

    An electromagnetic imaging system for metallic object detection and classification

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    PhD ThesisElectromagnetic imaging currently plays a vital role in various disciplines, from engineering to medical applications and is based upon the characteristics of electromagnetic fields and their interaction with the properties of materials. The detection and characterisation of metallic objects which pose a threat to safety is of great interest in relation to public and homeland security worldwide. Inspections are conducted under the prerequisite that is divested of all metallic objects. These inspection conditions are problematic in terms of the disruption of the movement of people and produce a soft target for terrorist attack. Thus, there is a need for a new generation of detection systems and information technologies which can provide an enhanced characterisation and discrimination capabilities. This thesis proposes an automatic metallic object detection and classification system. Two related topics have been addressed: to design and implement a new metallic object detection system; and to develop an appropriate signal processing algorithm to classify the targeted signatures. The new detection system uses an array of sensors in conjunction with pulsed excitation. The contributions of this research can be summarised as follows: (1) investigating the possibility of using magneto-resistance sensors for metallic object detection; (2) evaluating the proposed system by generating a database consisting of 12 real handguns with more than 20 objects used in daily life; (3) extracted features from the system outcomes using four feature categories referring to the objects’ shape, material composition, time-frequency signal analysis and transient pulse response; and (4) applying two classification methods to classify the objects into threats and non-threats, giving a successful classification rate of more than 92% using the feature combination and classification framework of the new system. The study concludes that novel magnetic field imaging system and their signal outputs can be used to detect, identify and classify metallic objects. In comparison with conventional induction-based walk-through metal detectors, the magneto-resistance sensor array-based system shows great potential for object identification and discrimination. This novel system design and signal processing achievement may be able to produce significant improvements in automatic threat object detection and classification applications.Iraqi Cultural Attaché, Londo

    Earth Resources: A continuing bibliography with indexes, issue 2

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    Reports, articles, and other documents announced between April and June 1974 in Scientific and Technical Aerospace Reports (STAR), and International Aerospace Abstracts (IAA) are cited. Documents related to the identification and evaluation by means of sensors in spacecraft and aircraft of vegetation, minerals, and other natural resources, and the techniques and potentialities of surveying and keeping up-to-date inventories of such riches are included along with studies of such natural phenomena as earthquakes, volcanoes, ocean currents, and magnetic fields; and such cultural phenomena as cities, transportation networks, and irrigation systems. The components and use of remote sensing and geophysical instrumentation, their subsystems, observational procedures, signature and analyses and interpretive techniques for gathering data are, described. All reports generated under NASA's Earth Resources Survey Program for the time period covered are included

    Advanced Sensing, Fault Diagnostics, and Structural Health Management

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    Advanced sensing, fault diagnosis, and structural health management are important parts of the maintenance strategy of modern industries. With the advancement of science and technology, modern structural and mechanical systems are becoming more and more complex. Due to the continuous nature of operation and utilization, modern systems are heavily susceptible to faults. Hence, the operational reliability and safety of the systems can be greatly enhanced by using the multifaced strategy of designing novel sensing technologies and advanced intelligent algorithms and constructing modern data acquisition systems and structural health monitoring techniques. As a result, this research domain has been receiving a significant amount of attention from researchers in recent years. Furthermore, the research findings have been successfully applied in a wide range of fields such as aerospace, manufacturing, transportation and processes
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