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

Millimetre wave imaging for concealed target detection

PhDConcealed weapon detection (CWD) has been a hot topic as the concern about pub- lic safety increases. A variety of approaches for the detection of concealed objects on the human body based on earth magnetic ¯eld distortion, inductive magnetic ¯eld, acoustic and ultrasonic, electromagnetic resonance, MMW (millimetre wave), THz, Infrared, x-ray technologies have been suggested and developed. Among all of them, MMW holographic imaging is considered as a promising approach due to the relatively high penetration and high resolution that it can o®er. Typical concealed target detection methods are classi¯ed into 2 categories, the ¯rst one is a resonance based target identi¯cation technique, and the second one is an imaging based system. For the former, the complex natural resonance (CNR) frequencies associated with a certain target are extracted and used for identi¯cation, but this technique has an issue of high false alarm rate. The microwave/millimetre wave imaging systems can be categorized into two types: passive systems and active sys- tems. For the active microwave/millimetre wave imaging systems, the microwave holographic imaging approach was adopted in this thesis. Such a system can oper- ate at either a single frequency or multiple frequencies (wide band). An active, coherent, single frequency operation millimetre wave imaging system based on the theory of microwave holography was developed. Based on literature surveys and ¯rst hand experimental results, this thesis aims to provide system level parame- ter determination to aid the development of a target detection imager. The goal is approached step by step in 7 chapters, with topics and issues addressed rang- ing from reviewing the past work, ¯nding out the best candidate technology, i.e. the MMW holographic imaging combined with the resonance based target recog- i nition technique, the construction of the 94 GHz MMW holographic prototype imager, experimental trade-o® investigation of system parameters, imager per- formance evaluation, low pro¯le components and image enhancement techniques, feasibility investigation of resonance based technique, to system implementation based on the parameters and results achieved. The task set forth in the beginning is completed by coming up with an entire system design in the end.

The use of late time response for stand off onbody concealed weapon detection

A new system for remote detection of onbody concealed weapons such as knives and handheld guns at standoff distances presented in this thesis. The system was designed, simulated, constructed and tested in the laboratory. The detection system uses an Ultrawide Band (UWB) antenna to bombard the target with a UWB electromagnetic pulse. This incident pulse induces electrical currents in the surface of an object such as a knife, which given appropriate conditions these currents generate an electromagnetic backscatter radiation. The radiated waves are detected using another UWB antenna to obtain the Late Time Response (LTR) signature of the detected object. The LTR signature was analysed using the Continuous Wavelet Transform (CWT) in order to assess the nature and the geometry of the object. The thesis presents the work which divided into two related areas. The first involved the design, simulation, fabrication, and testing of an Ultra-wide Band (UWB) antenna with operating bandwidth of 0.25 – 3.0 GHz and specific characteristics. Simulated and measured results show that the designed antenna achieves the design objectives which are, flat gain, a VSWR of around unity and distortion less transmitted narrow pulse. The operating bandwidth was chosen to cover the fundamental Complex Natural Resonance (CNR) modes of most firearms and to give a fine enough time resolution. The second area covered by this thesis presents a new approach for extract target signature based on the Continuous Wavelet Transform (CWT) applied to the scattering response of onbody concealed weapons. A series of experiments were conducted to test the operation of the detection system which involved onbody and offbody objects such as, knives, handheld guns, and a number of metallic wires of various dimensions. Practical and simulation results were in good agreement demonstrating the success of the approach of using the CWT in analyzing the LTR signature which is used for the first time in this work. Spectral response for every target could be seen as a distribution in which the energy level and life-time depended on the target material and geometry. The spectral density provides very powerful information concerning target unique signature

Concealed Explosives Detection using Swept Millimetre Waves

The aim of this project is to develop a system for the stand-o detection (typically ten metres) of concealed body-worn explosives. The system must be capable of detecting a layer of explosive material hidden under clothing and distinguishing explosives from everyday objects. Millimetre wave radar is suitable for this application. Millimetre Waves are suitable because they are not signi cantly attenuated by atmospheric con- ditions and clothing textiles are practically transparent to this radiation. Detection of explosive layers from a few mm in thickness to a few cm thickness is required. A quasi optical focussing element is required to provide su cient antenna directivity to form a narrow, highly directional beam of millimetre waves, which can be directed and scanned over the person being observed. A system of antennae and focussing optics has been modelled and built using designs from nite element analysis (FEA) software. Using the developed system, represen- tative data sets have been acquired using a Vector Network Analyser (VNA) to act as transmitter and receiver, with the data saved for processing at a later time. A novel data analysis algorithm using Matlab has been developed to carry out Fourier Transforms of the data and then perform pattern matching techniques using arti cial neural networks (ANN's). New ways of aligning and sorting data have been found using cross-correlation to order the data by similar data slices and then sorting the data by amplitude to take the strongest 50% of data sets. The signi cant contribution to knowledge of this project will be a system which can be eld tested and which will detect a layer of dielectric at a stando distance, typically of ten metres, and signal processing algorithms which can recognise the di erence 17 between the response of threat and non-threat objects. This has partially been achieved by the development of focussing optics to acquire data sets which have then been aligned by cross-correlation, sorted and then used to train a pattern matching technique using neural networks. This technique has shown good results in di erentiating between a person wearing simulated explosives and a person not carrying simulated explosives. Further work for this project includes acquiring more data sets of everyday objects and training the neural network to distinguish between threat objects and non-threat objects. The operational range also needs increasing using either a larger aperture optical element or a similarly sized Cassegrain antenna. The system needs adapting for real time use with the data processing techniques developed in Matlab. The VNA is operated over a band of 14 to 40 GHz, future work includes moving to a stand-alone transmitter and receiver operating at w-band (75 to 110 GHz)

Investigation of late time response analysis for security applications

The risk of armed attack by individual’s intent on causing mass casualties against soft targets, such as transport hubs continues. This has led to an increased need for a robust, reliable and accurate detection system for concealed threat items. This new system will need to improve upon existing detection systems including portal based scanners, x-ray scanners and hand held metal detectors as these all suffer from drawbacks of limited detection range and relatively long scanning times. A literature appraisal has been completed to assess the work being undertaken in the relevant field of Concealed Threat Detection (CTD). From this Ultra-Wide Band (UWB) radar has been selected as the most promising technology available for CTD at the present. UWB radar is provided by using Frequency Modulated Continuous Waves (FMCW) from laboratory test equipment over a multi gigahertz bandwidth. This gives the UWB radar the ability to detect both metallic and dielectric objects. Current published results have shown that it is possible to use the LTR technique to detect and discriminate both single objects isolated in air and multiple objects present within the same environment. A Vector Network Analyser (VNA) has been used to provide the Ultra-Wide Band (UWB) Frequency Modulated Continuous Wave (FMCW) radar signal required for the LTR technique. This thesis presents the application of the Generalized Pencil-of-Function (GPOF), Dual Tree Wavelet Transform (DTWT) and the Continuous Wavelet Transform (CWT), both real and complex valued, in Late Time Response (LTR) security analysis to produce a viable detection algorithm. Supervised and unsupervised Artificial Neural Networks (ANN) have been applied to develop a successful classification scheme for Concealed Threat Detection (CTD) in on body security screening. Signal deconvolution and other techniques have been applied in post processing to allow for extraction of the LTR signal from the scattered return. Data vectorization has been applied to the extracted LTR signal using an unsupervised learning based ANN to prepare data for classification. Classification results for both binary threat/non-threat classifiers and a group classifier are presented. The GPOF method presented true positive classification results approaching 72% with wavelet based methods offering between 98% and 100%

Finite element analysis approach to open area concealed weapon detection system

Individuals carrying threat objects inside secured areas possess significant risk to security of establishments and safety of public. Traditional weapon inspection equipment is limited in portability and requires trained operators in confined security checkpoints. Although various methods to screen people for threat objects have been employed at secured establishments, screening equipment and procedures have not been designed to work in open spaces like airport check-in areas, hospitals, schools and university entrances. Coupled to this, relatively large numbers of false alarms from non-threat metal objects are identified as a threat by the current Concealed Weapon Detection (CWD) screening equipment, is a major cause of concern and is associated with higher operational costs. Hence, the design and development of a concealed weapon detection system, with reduced false alarms and increased detection along with classification capability that can operate in a large open area is essential. A comprehensive numerical model of a CWD system, using the Finite Element Analysis (FEA) method, to detect and classify metal objects with accuracy within a single zone of a multi zone Open Area CWD (OACWD) system, was developed. A mathematical model was developed and applied to the time-domain transient electromagnetic field, which are modelled and simulated using FEA methods. The methods were then applied to a single zone of a multi zone OACWD system to create an object signature database utilising the decay time constant; a unique property of metal objects in time-domain transient electromagnetic fields. The objects were detected by the unique signature property in OACWD system, Since early and intermediate stages was found contain object signatures, receiver current for these stages are digitised and stored in a weapon database, which is then used to match target for identification within the OACWD system. The thesis analyses the following characteristics of a single zone OACWD system; target material variation, target shape (both geometric and common weapon shape) variation, size, rotational variation, proximity variation of targets, the successful estimation and comparison of these parameters lead to classification of metal objects in OACWD system. This work also explores the characteristic properties and components of OACWD models such aspublic safety and the privacy of individuals using the system. The system, when integrated with other screening devices, e.g. Close Circuit Television (CCTV) monitoring system, is able to find individuals with threat objects in real-time detection space. Summarizing, In this thesis work, single zone detection system was designed by developing have developed an electromagnetic circuit to design, which can successfully detect threat metal objects irrespective of their orientation based on time constant decay. This system is a significant advance over the existing portal based detection system, as it would reduce the incidence of false alarms and traffic congestion at the security establishment

Remote Detection of Concealed Guns and Explosives

A reliable method of remotely detecting concealed guns and explosives attached to the human body is of great interest to governments and security forces throughout the world. This thesis describes the development and trials of a new remote non-imaging concealed threat detection method using active millimetre wave radar using the microwave and mmwave frequencies bands 14 – 40 and 75 – 110 GHz (Ku, K, Ka and W). The method is capable of not only screening for concealed objects, like the current generation of concealed object detectors, but also of differentiating between mundane and threat objects. The areas focused upon during this investigation were: identifying the impact of different commonly worn fabrics as barriers to detection; consulting with end users about their requirements and operational needs; a comparison of different frequency bands for the detection of guns and explosives; exploring the effects of polarisation on object detection; a performance comparison of different detection schemes using Artificial Neural Networks; improving existing data acquisition systems and prototyping of a real-time capture system

Development of techniques and technology for full polarimetric radar applied to concealed weapons detection

One of the biggest threats to modern society is the increasing use by criminals and terrorists of concealed weapons and person born improvised explosive devices (PBIED). Current highly mature security screening technologies using x-ray and metal detectors have limited deployment scenarios based on health and safety issues and operational range, respectively. Given that most clothing is greater than 90% transmissive in the microwave region, this spectral band is ideal for screening people for concealed threats. However, due to diffraction, imagery to screen subjects is limited due to the small number of pixels. In this regime, the exploitation of microwave polarimetry from the field of remote sensing has particular benefits, as it extracts maximum information content from a single pixel. The work presented in this thesis has assembled a full polarimetric frequency stepped radar from a vector network analyser (VNA), a linear orthogonal mode transducer (OMT) of the turnstile type and a conical corrugated horn antenna. The system’s characterisation by antenna pattern measurements, the measuring of canonical targets of the plane, dihedral, dipole and helical reflectors showed the system to be capable of making localised Sinclair matrix measurements of targets at ranges of two to three metres. The work presents a calibration procedure comprising the VNA’s internal calibration and an external calibration to compensate for dispersion and cross-polar leakage of system components. Static target measurements (canonical and various surrogate items) were analysed, using range gating for clutter rejection. Calibrated Sinclair parameter measurements compared with those from simple simulations, all software being programmed in Matlab. Measurements of moving targets revealed the phenomenon of speckle, this introducing rapid changes in the Sinclair Parameters. Data analysis performed using the coherency matrix and the Cloude/Pottier decomposition minimised the effects of speckle in the processed data. Measurements show movement from particularly rough surfaces increased the parameter of the Cloude/Pottier entropy, the level of this being directly linked to the degree of speckle. Application of the Huynen polarisation fork technique (a type of decomposition) has proved to aid the identification of static and moving targets. A detailed analysis of iii the Huynen fork responses is made of the human torso on its own, weapons on their own and then weapons positioned against the human torso. Responses of nondangerous objects such as keys and a smartphone are additionally presented