Short-Range Super-Resolution Feature Extraction of Complex Edged Contours for Object Recognition by Ultra-Wideband Radar

This thesis contributes to the field of short-range ultra-wideband (UWB) Radar. In particular, an object recognition approach performed by a bi-static UWB Radar has been investigated in this thesis. The investigated objects consist of simple canonical and some polygonal complex objects which are scanned on a circular track at about 1 m distance. Geometrical features, texture features and moment based features are extracted from the Radar data to carry out the recognition. Yet, the precise temporal evolution is subject to massive distortions, mainly caused by severe interference conditions and transient effects of the hardware. Thus, super-resolution algorithms have been developed which go far beyond the classical bandwidth given resolution and asked for research on various fields: (i) An innovative wavefront extraction algorithm with polarimetric diversity exploitation has been developed to separate pulses which overlap almost the whole pulse duration; (ii) a highly precise feature extraction algorithm has been developed which localises significant scattering centres by processing the previously extracted wavefronts; (iii) a novel UWB object recognition algorithm has been developed to classify and discriminate the resulting microwave images. When scanning objects from all sides, exceptional recognition of objects was achieved by a minimum mean squared error classifier. Further improvement in recognition was obtained, especially at severly restricted tracks, by the application of Bayes theory which constitutes a superior classifier to the above. In addition to the main field of research, a novel stereoscopic 3D UWB imaging algorithm, based on a spatially spanned synthetic aperture in conjunction with ellipsoidal shaped wavefronts, has been developed. The ultimate test of any model and system is an experimental validation. Consequently in this thesis, all developed algorithms and the object recognition as a whole system are experimentally validated within an elaborate measurement campaign

Evolution of Communication and Monitoring Systems for the Management of Traffic and Safety Control Systems in Railway Sites

The collaboration between R.F.I. S.p.A. and Alma Mater Studiorum of Bologna had the purpose to evaluate the feasibility and to investigate the main radar sensor tech- nologies suited to be integrated with existing signalling systems in rail sites, with particular reference to the UWB technology. This activity has been supported by a study of the UWB radio channel characteristics in a reference (LC-like) scenario, through ray tracing (RT) simulation. It was also studied, with the aid of computer simulations, the remote interconnection of several radars via fiber optic links (RoF), in order to concentrate in a single physical location all the signal processing operations and network control

DEVELOPMENT OF AN UWB RADAR SYSTEM

An ultra-wideband radar system is built at the University of Tennessee with the goal to develop a ground penetrating radar (GPR). The radar is required to transmit and receive a very narrow pulse signal in the time domain. The bistatic radar transmits a pulse through an ultrawide spiral antenna and receives the pulse by a similar antenna. Direct sampling is used to improve the performance of the impulse radar allowing up to 1.5 GHz of bandwidth to be used for signal processing and target detection with high resolution. Using direct sampling offers a less complex system design than traditional lower sample rate, super-heterodyne systems using continuous wave or step frequency methods while offering faster results than conventional equivalent time sampling techniques that require multiple data sets and significant post-processing. These two points are particularly important for a system that may be used in the field in potentially dangerous environments. Direct sampling radar systems, while still frequency limited, are continually improving their upper frequencies boundaries due to more power efficient, higher sampling rate analog to digital converters (ADCs) which relates directly to better subsurface resolution for potential target detection

The analysis of UWB Radar System for Microwave Imaging Application.

PhDMany research groups have conducted the investigation into UWB imaging radar system for various applications over the last decade. Due to the demanding security requirements, it is desirable to devise a convenient and reliable imaging system for concealed weapon detection. Therefore, this thesis presents my research into a low cost and compact UWB imaging radar system for security purpose. This research consists of two major parts: building the UWB imaging system and testing the imaging algorithms. Firstly, the time-domain UWB imaging radar system is developed based on a modulating scheme, achieving a receiver sensitivity of -78dBm and a receiver dynamic range of 69dB. A rotary UWB antenna linear array, comprising one central transmitting antenna and four side-by-side receiving antennas, is adopted to form 2D array in order to achieve a better cross-range resolution of the target. In operation, the rotation of the antenna array is automatically controlled through the computerised modules in LabVIEW. Two imaging algorithms have been extensively tested in the developed UWB radar system for a number of scenarios. In simulation, the “Delay and Sum (DAS)” method has been shown to be effective at mapping out the metallic targets in free space, but prone to errors in more complicated environments. However, the “Time Reversal (TR)” method can produce better images in more complex scenarios, where traditionally unfavorable multi-path interference becomes a valuable asset. These observations were verified in experiment in different testing environments, such as penetration through wooden boards, clutters and a stuffed sport bag. The detectable size of a single target is 8×8×1 cm3 with 30cm distance in a stuffed bag, while DAS can achieve the estimation of 7cm cross-range resolution and 15cm down-range resolution for two targets with sizes of 8×8×1 cm3 and 10×10×1 cm3, which fits within the theoretical prediction. In contrast, TR can distinguish them with a superior 4cm cross range resolution

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

Microwave Sensing and Imaging

In recent years, microwave sensing and imaging have acquired an ever-growing importance in several applicative fields, such as non-destructive evaluations in industry and civil engineering, subsurface prospection, security, and biomedical imaging. Indeed, microwave techniques allow, in principle, for information to be obtained directly regarding the physical parameters of the inspected targets (dielectric properties, shape, etc.) by using safe electromagnetic radiations and cost-effective systems. Consequently, a great deal of research activity has recently been devoted to the development of efficient/reliable measurement systems, which are effective data processing algorithms that can be used to solve the underlying electromagnetic inverse scattering problem, and efficient forward solvers to model electromagnetic interactions. Within this framework, this Special Issue aims to provide some insights into recent microwave sensing and imaging systems and techniques

UWB Pulse Radar for Human Imaging and Doppler Detection Applications

We were motivated to develop new technologies capable of identifying human life through walls. Our goal is to pinpoint multiple people at a time, which could pay dividends during military operations, disaster rescue efforts, or assisted-living. Such system requires the combination of two features in one platform: seeing-through wall localization and vital signs Doppler detection. Ultra-wideband (UWB) radar technology has been used due to its distinct advantages, such as ultra-low power, fine imaging resolution, good penetrating through wall characteristics, and high performance in noisy environment. Not only being widely used in imaging systems and ground penetrating detection, UWB radar also targets Doppler sensing, precise positioning and tracking, communications and measurement, and etc. A robust UWB pulse radar prototype has been developed and is presented here. The UWB pulse radar prototype integrates seeing-through imaging and Doppler detection features in one platform. Many challenges existing in implementing such a radar have been addressed extensively in this dissertation. Two Vivaldi antenna arrays have been designed and fabricated to cover 1.5-4.5 GHz and 1.5-10 GHz, respectively. A carrier-based pulse radar transceiver has been implemented to achieve a high dynamic range of 65dB. A 100 GSPS data acquisition module is prototyped using the off-the-shelf field-programmable gate array (FPGA) and analog-to-digital converter (ADC) based on a low cost solution: equivalent time sampling scheme. Ptolemy and transient simulation tools are used to accurately emulate the linear and nonlinear components in the comprehensive simulation platform, incorporated with electromagnetic theory to account for through wall effect and radar scattering. Imaging and Doppler detection examples have been given to demonstrate that such a “Biometrics-at-a-glance” would have a great impact on the security, rescuing, and biomedical applications in the future

Novel Hybrid-Learning Algorithms for Improved Millimeter-Wave Imaging Systems

Increasing attention is being paid to millimeter-wave (mmWave), 30 GHz to 300 GHz, and terahertz (THz), 300 GHz to 10 THz, sensing applications including security sensing, industrial packaging, medical imaging, and non-destructive testing. Traditional methods for perception and imaging are challenged by novel data-driven algorithms that offer improved resolution, localization, and detection rates. Over the past decade, deep learning technology has garnered substantial popularity, particularly in perception and computer vision applications. Whereas conventional signal processing techniques are more easily generalized to various applications, hybrid approaches where signal processing and learning-based algorithms are interleaved pose a promising compromise between performance and generalizability. Furthermore, such hybrid algorithms improve model training by leveraging the known characteristics of radio frequency (RF) waveforms, thus yielding more efficiently trained deep learning algorithms and offering higher performance than conventional methods. This dissertation introduces novel hybrid-learning algorithms for improved mmWave imaging systems applicable to a host of problems in perception and sensing. Various problem spaces are explored, including static and dynamic gesture classification; precise hand localization for human computer interaction; high-resolution near-field mmWave imaging using forward synthetic aperture radar (SAR); SAR under irregular scanning geometries; mmWave image super-resolution using deep neural network (DNN) and Vision Transformer (ViT) architectures; and data-level multiband radar fusion using a novel hybrid-learning architecture. Furthermore, we introduce several novel approaches for deep learning model training and dataset synthesis.Comment: PhD Dissertation Submitted to UTD ECE Departmen