619 research outputs found
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
Improving the Convergence of Vector Fitting for Equivalent Circuit Extraction From Noisy Frequency Responses
The vector fitting (VF) algorithm has become a common tool in electromagnetic compatibility and signal integrity studies. This algorithm allows the derivation of a rational approximation to the transfer matrix of a given linear structure starting from measured or simulated frequency responses. This paper addresses the convergence properties of a VF when the frequency samples are affected by noise.We show that small amounts of noise can seriously impair or destroy convergence. This is due to the presence of spurious poles that appear during the iterations. To overcome this problem we suggest a simple modification of the basic VF algorithm, based on the identification and removal of the spurious poles. Also, an incremental pole addition and relocation process is proposed in order to provide automatic order estimation even in the presence of significant noise.We denote the resulting algorithm as vector fitting with adding and skimming (VF-AS). A thorough validation of the VF-AS algorithm is presented using a Monte Carlo analysis on synthetic noisy frequency responses. The results show excellent convergence and significant improvements with respect to the basic VF iteration scheme. Finally, we apply the new VF-AS algorithm to measured scattering responses of interconnect structures and networks typical of high-speed digital systems
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
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%
Radar Technology
In this book “Radar Technology”, the chapters are divided into four main topic areas: Topic area 1: “Radar Systems” consists of chapters which treat whole radar systems, environment and target functional chain. Topic area 2: “Radar Applications” shows various applications of radar systems, including meteorological radars, ground penetrating radars and glaciology. Topic area 3: “Radar Functional Chain and Signal Processing” describes several aspects of the radar signal processing. From parameter extraction, target detection over tracking and classification technologies. Topic area 4: “Radar Subsystems and Components” consists of design technology of radar subsystem components like antenna design or waveform design
Modelling and detection of faults in axial-flux permanent magnet machines
The development of various topologies and configurations of axial-flux permanent magnet machine has spurred its use for electromechanical energy conversion in several applications. As it becomes increasingly deployed, effective condition monitoring built on reliable and accurate fault detection techniques is needed to ensure its engineering integrity. Unlike induction machine which has been rigorously investigated for faults, axial-flux permanent magnet machine has not. Thus in this thesis, axial-flux permanent magnet machine is investigated under faulty conditions. Common faults associated with it namely; static eccentricity and interturn short circuit are modelled, and detection techniques are established. The modelling forms a basis for; developing a platform for precise fault replication on a developed experimental test-rig, predicting and analysing fault signatures using both finite element analysis and experimental analysis. In the detection, the motor current signature analysis, vibration analysis and electrical impedance spectroscopy are applied. Attention is paid to fault-feature extraction and fault discrimination. Using both frequency and time-frequency techniques, features are tracked in the line current under steady-state and transient conditions respectively. Results obtained provide rich information on the pattern of fault harmonics. Parametric spectral estimation is also explored as an alternative to the Fourier transform in the steady-state analysis of faulty conditions. It is found to be as effective as the Fourier transform and more amenable to short signal-measurement duration. Vibration analysis is applied in the detection of eccentricities; its efficacy in fault detection is hinged on proper determination of vibratory frequencies and quantification of corresponding tones. This is achieved using analytical formulations and signal processing techniques. Furthermore, the developed fault model is used to assess the influence of cogging torque minimization techniques and rotor topologies in axial-flux permanent magnet machine on current signal in the presence of static eccentricity. The double-sided topology is found to be tolerant to the presence of static eccentricity unlike the single-sided topology due to the opposing effect of the resulting asymmetrical properties of the airgap. The cogging torque minimization techniques do not impair on the established fault detection technique in the single-sided topology. By applying electrical broadband impedance spectroscopy, interturn faults are diagnosed; a high frequency winding model is developed to analyse the impedance-frequency response obtained
Microwave imaging for ultra-wideband antenna based cancer detection
Breast cancer is one of the most widespread types of cancer in the world. The key
factor in treatment is to reliably diagnose the cancer in the early stages. Moreover,
currently used clinical diagnostic methods, such as X-ray, ultra-sound and MRI, are
limited by cost and reliability issues. These limitations have motivated researchers to
develop a more effective, low-cost diagnostic method and involving lower ionization
for cancer detection. In this thesis, radar based microwave imaging is proposed as a
method for early breast cancer detection. This imaging system has advantages such as
low cost, being non- invasive and easy to use, with high image resolution and its thus
good potential for early cancer detection.
In the first stage, an ultra-wideband Vivaldi antenna and a slot Vivaldi antenna are
proposed, simulated and fabricated for breast cancer detection. The designed antennas
exhibit an ultra-wideband working frequency. The radiation patterns also achieve the
desired directional radiation patterns.
The second stage of this study presents a planar breast phantom and a hemisphere
breast phantom. These two breast phantoms are simulated and fabricated using CST
microwave studio and tissue-mimicking materials respectively. Mono-static radar
systems based on a single antenna configuration and an antenna pair configuration are
then proposed. These two systems are used to measure the planar breast phantom and
hemi- sphere breast phantom, with the scattering signals measured in the frequency
and time domains. Based on the measurement results, it is concluded that the reflected
energy increases when the antenna moves close to the tumour; otherwise, the reflected
energy is reduced when the antenna moves away from the tumour.
The received time domain scattering signals are processed first and then used to
create microwave images to indicate tumour position. A clutter removal method is
proposed to extract the tumour response from the received signals. The microwave
images are then created using the tumour response based on the simulation and
experimental results. The imaging results indicate that a 5 mm radius tumour can be
detected.
The tumour burial depth is also studied. A multi bio- layer phantom which contains
deep and shallow buried tumours is simulated and measured using the Vivaldi antenna.
A spectrum analysis method is proposed to distinguish between different tumour
depths. The results indicate that a difference in depth of 15 mm results in a mean
change of 0.3 dB in the magnitude of the spectrum.
Discrimination between benign and malignant tumours is also considered in this
study. The singularity expansion method (SEM) for breast cancer is proposed to
discriminate between benign and malignant tumours based on their morphology. Two
cancerous breast phantoms are developed in CST. The benign tumour is a 5mm radius
sphere and the malignant tumour is a spiny sphere with an average radius of 5mm.
The use of the SEM leads to the successful discrimination of these two tumours. This
method provides a solution to discriminate between benign and malignant tumours
similar size when the resulting images cannot provide sufficient resolution.
A preliminary study of brain cancer detection is also concluded. Research in this
area has never been implemented. A cancerous brain model is designed and simulated
in CST. The antenna pair configuration is then used to measure the cancerous brain,
with the scattering signals measured. Microwave images for brain cancer detection are
then created based on the measurement results. The tumour is correctly indicated in
the resulting images
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