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.

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

Indoor Full-Body Security Screening: Radiometric Microwave Imaging Phenomenology and Polarimetric Scene Simulation

The paper discusses the scene simulation of radiometric imagers and its use to illustrate the phenomenology of full-body screening of people for weapons and threats concealed under clothing. The aperture synthesis technique is introduced as this offers benefits of wide field-of-views and large depths-of-fields in a system that is potentially conformally deployable in the confined spaces of building entrances and at airport departure lounges. The technique offers a non-invasive, non-cooperative screening capability to scrutinize all human body surfaces for illegal items. However, for indoor operation, the realization of this capability is challenging due to the low radiation temperature contrasts in imagery. The contrast is quantified using a polarimetric radiometric layer model of the clothed human subject concealing threats. A radiation frequency of 20 GHz was chosen for the simulation as system component costs here are relatively low and the attainable half-wavelength spatial resolution of 7.5 mm is sufficient for screening. The contrasts against the human body of the threat materials of metal, zirconia ceramic, carbon fiber, nitrogen-based energetic materials, yellow beeswax, and water were calculated to be ≤7 K. Furthermore, the model indicates how some threats frequency modulate the radiation temperatures by ~ ±1 K. These results are confirmed by experiments using a radiometer measuring left-hand circularly polarized radiation. It is also shown using scene simulation how circularly polarized radiation has benefits for reducing false alarms and how threat objects appear in canyon regions of the body, such as between the legs and in the armpits

Microwave imaging for security applications

Microwave imaging technologies have been widely researched in the biomedical field where they rely on the imaging of dielectric properties of tissues. Healthy and malignant tissue have different dielectric properties in the microwave frequency region, therefore, the dielectric properties of a human body’s tissues are generally different from other contraband materials. Consequently, dielectric data analysis techniques using microwave signals can be used to distinguish between different types of materials that could be hidden in the human body, such as explosives or drugs. Other concerns raised about these particular imaging systems were how to build them cost effectively, with less radiation emissions, and to overcome the disadvantages of X-ray imaging systems. The key challenge in security applications using microwave imaging is the image reconstruction methods adopted in order to gain a clear image of illuminated objects inside the human body or underneath clothing. This thesis will discuss in detail how microwave tomography scanning could overcome the challenge of imaging objects concealed in the human body, and prove the concept of imaging inside a human body using image reconstruction algorithms such as Radon transformation image reconstruction. Also, this thesis presents subspace based TR-MUSIC algorithms for point targets and extended targets. The algorithm is based on the collection of the dominant response matrix reflected by targets at the transducers in homogenous backgrounds, and uses the MUSIC function to image it. Lumerical FDTD solution is used to model the transducers and the objects to process its response matrix data in Matlab. Clear images of metal dielectric properties have been clearly detected. Security management understanding in airports is also discussed to use new scanning technologies such as microwave imaging in the future.The main contribution of this reseach is that microwave was proved to be able to image and detect illegal objects embedded or implanted inside human body

Body shape-based biometric person recognition from mmW images

A growing interest has arisen in the security community for the use of millimeter waves in order to detect weapons and concealed objects. Also, the use of millimetre wave images has been proposed recently for biometric person recognition to overcome certain limitations of images acquired at visible frequencies. This paper proposes a biometric person recognition system based on shape information extracted from millimetre wave images. To this aim, we report experimental results using millimeter wave images with different body shape-based feature approaches: contour coordinates, shape contexts, Fourier descriptors and row and column profiles, using Dynamic Time Warping for matching. Results suggest the potential of performing person recognition through millimetre waves using only shape information, a functionality that could be easily integrated in the security scanners deployed in airportsThis work has been partially supported by project CogniMetrics TEC2015-70627-R (MINECO/FEDER), and the SPATEK network (TEC2015-68766-REDC

3D Holographic Millimeter-Wave Imaging for Concealed Metallic Forging Objects Detection

This chapter investigates the feasibility of using 3D holographic millimeter-wave (HMMW) imaging for diagnosis of concealed metallic forging objects (MFOs) in inhomogeneous medium. A 3D numerical system, including radio frequency (RF) transmitters and detectors, various realistic MFOs models and signal and imaging processing, is developed to analyze the measured data and reconstruct images of target MFOs. Simulation and experimental validations are performed to evaluate the HMMW approach for diagnosis of concealed MFOs. Results show that various concealed objects can be clearly represented in the reconstructed images with accurate sizes, locations and shapes. The proposed system has the potential for further investigation of concealed MFOs under clothing in the future, which has the potential applications in on body concealed weapon detection at security sites or MFOs detection in children

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)

Shape and deformation measurement using heterodyne range imaging technology

Range imaging is emerging as a promising alternative technology for applications that require non-contact visual inspection of object deformation and shape. Previously, we presented a solid-state full-field heterodyne range imaging device capable of capturing three-dimensional images with sub-millimetre range resolution. Using a heterodyne indirect time-of-flight configuration, this system simultaneously measures distance (and intensity), for each pixel in a cameras field of view. In this paper we briefly describe our range imaging system, and its principle of operation. By performing measurements on several metal objects, we demonstrate the potential capabilities of this technology for surface profiling and deformation measurement. In addition to verifying system performance, the reported examples highlight some important system limitations. With these in mind we subsequently discuss the further developments required to enable the use of this device as a robust and practical tool in non-destructive testing and measurement applications

Development of Scale and Rotation Invariant Neural Network based Technique for Detection of Dielectric Contrast Concealed Targets with Millimeter Wave System

The detection of concealed targets beneath a person’s clothing from standoff distance is an important task for protection and the security of a person in a crowded place like shopping malls, airports and playground stadium, etc. The detection capability of the concealed weapon depends on a lot of factors likes, a collection of back scattered data, dielectric property and a thickness of covering cloths, the hidden object, standoff distance and the probability of false alarm owing to objectionable substances. Though active millimeter wave systems have used to detect weapons under cloths, but still more attention is required to detect the target likes a gun, knife, and matchbox. To observe such problems, active V-band (59 GHz- 61 GHz) MMW radar with the help of artificial neural network (ANN) has been demonstrated for non-metallic as well as metallic concealed target detection. To validate ANN, the signature of predefined targets is matched with the signature of validated data with the help of the correlation coefficient. The proposed technique has good capability to distinguish concealed targets under various cloths.

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