Classification of Metallic Targets Using a Walk-Through Metal Detection Portal

Metal detectors have been used for a long time for treasure hunting, security screening, and finding buried objects such as landmines or unexploded ordnance. Walk-through metal detection (WTMD) portals are used for making sure that forbidden or threatening metallic items, such as knives or guns, are not carried into secure areas at critical locations such as airports, court rooms, embassies, and prisons.The 9/11 terrorist act has given rise to stricter rules for aviation security worldwide, and the ensuing tighter security procedures have meant that passengers face more delays at airports. Moreover, the fear of terrorism has led to the adoption of security screening technology in a variety of places such as railway and coach stations, sports events, malls, and nightclubs.However, the current WTMD technology and scanning procedures at airports require that all metallic items be removed from clothing prior to scanning, causing inconvenience. Furthermore, alarms are triggered by innocuous items such as shoe shanks and artificial joints, along with overlooked items such as jewellery and belts. These lead to time- consuming, manual pat-down searches, which are found inconvenient, uncomfortable, and obtrusive by some.Modern WTMD portals are very sensitive devices that can detect items with only small amounts of metal, but they currently lack the ability to further classify the detected item. However, if a WTMD portal were able to classify objects reliably into, e.g., “knives”, “belts”, “keys”, the need for removing the items prior to screening would disappear, enabling a paradigm shift in the field of security screening.This thesis is based on novel research presented in five peer-reviewed publications. The scope of the problem has been narrowed down to a situation in which only one metallic item is carried through the portal at a time. However, the methods and results presented in this thesis can be generalized into a multi-object scenario. It has been shown that by using a WTMD portal and the magnetic polarisability tensor, it is possible to accurately distinguish between threatening and innocuous targets and to classify them into 10 to 13 arbitrary classes. Furthermore, a data library consisting of natural walk-throughs has been collected, and it has been demonstrated that the walk-through data collected with the above portal are subject to phenomena that might affect classification, in particular a bias and the so-called body effect. However, the publications show that, by using realistic walk-through data, high classification accuracy can be maintained regardless of the above problems. Furthermore, a self-diagnostics method for detecting unreliable samples has also been presented with potential to significantly increase classification accuracy and the reliability of decision making.The contributions presented in this thesis have a variety of implications in the field of WTMD-based security screening. The novel technology offers more information, such as an indication of the probable cause of the alarm, to support the conventional screening procedure. Moreover, eliminating the need for removing all metallic items prior to screening enables design of new products for scenarios such as sports events, where conventional screening procedures might be inconvenient, creating thus new business possibilities for WTMD manufacturing companies.The positive results give rise to a variety of future research topics such as using wideband data, enabling simultaneous classification of multiple objects, and developing the portal coil design to diminish signal nonlinearities. Furthermore, the ideas and the basic principles presented in this thesis may be applied to other metal detection applications, such as humanitarian demining

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

Aspect independent detection and discrimination of concealed metal objects by electromagnetic pulse induction: a modelling approach

The work presented in this thesis describes the research, modelling and experimentation which were carried out so as to explore the use of electromagnetic pulse induction for the detection of nearby or on-body threat items such as handguns and knives. Commercially available finite difference time domain electromagnetic solver software, Vector Fields, was used to simulate the interaction of a low frequency electromagnetic pulse with different metal objects. The ability to discriminate between objects is based on the lifetime of the induced currents in the object, typically around 100 (μs). Lifetimes are different for a different objects, whether they are weapons or benign objects. For example hand grenades, knives, and handguns are clearly threat objects whereas a wrist watch, mobile phone and keys are considered benign. Electromagnetic pulse Induction (EMI) relies on generating a time-changing but spatially uniform magnetic field, which penetrates and encompasses a concealed metallic object. The temporally changing magnetic field induces eddy currents in the conducting object, which subsequently decay by dissipative (i.e. resistive) losses. These currents decay exponentially with time and exhibit a characteristic time constant (lifetime) which depends only upon the size, shape and material composition of the object, whilst the orientation of the object is irrelevant. This aspect independence of temporal current decay rates forms the basis of a potential object detection and identification system. This thesis investigates the possibility of detecting, resolving and identifying multiple objects if they are close together, for example located on an individual. The mathematical analysis used for the investigation implements the generalised pencil of function (GPOF) method. The GPOF algorithm decomposes the signal into a discrete set of complex frequency components; providing the capability to obtain the time constants from data. It was possible to effectively count and identify multiple metallic objects carried in close proximity providing that the objects do not have very similar time constants. The simulation results, which show that multiple objects can be detected, resolved and identified by means of their time constants even when they are close together, are presented

A Flag-Based Algorithm for Explosives Detection in Sea-Land Cargo Containers using Active Neutron Interrogation.

The high volume and minimal screening of sea land cargo containers presents a vulnerability in which explosive devices may be smuggled across national borders. Fast neutrons are a strong candidate for use in container screening due to their high target penetration and ability to discriminate between materials of low atomic mass, such as explosives and non metallic container contents. An algorithm has been developed that uses flags, calculated from specific measurements of the reflected neutrons and photons produced during active neutron interrogation, to discern explosives hidden in cargo containers. Steps in algorithm development included Monte Carlo simulations for scatter characterization, identification of flags in idealized scenarios, refinement of flags in realistic scenarios, combining the flags into a detection algorithm, and evaluation of the algorithm and associated detection system. Simulations compared favorably with small scale neutron scatter measurements using the explosives surrogate, melamine. The detection algorithm included corrections for different types of cargo contents and cargo inhomogeneity, surrounding environment, and realistic neutron sources and radiation detectors. The proposed algorithm has two variations, one of which can be easily implemented with today’s technology. The proposed scanning system utilizes a shielded 14.1 MeV neutron generator, eleven large liquid scintillators neutron detectors, and several inorganic scintillators for photon spectroscopy. This system should cost less than $1M to install and dose estimates fall well within acceptable levels for both operators and smuggled persons. Algorithm performance has been quantified with various explosive sizes and positions, as well as heterogeneous cargo configurations, with typical minimum detectable amounts not exceeding 200 kg.Ph.D.Nuclear Engineering & Radiological SciencesUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/91602/1/alehnert_1.pd

An electromagnetic imaging system for metallic object detection and classification

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