Development of a Real-time Ultra-wideband See Through Wall Imaging Radar System

Ultra-Wideband (UWB) See-Through-Wall (STW) technology has emerged as a musthave enabling technology by both the military and commercial sectors. As a pioneer in this area, we have led the research in addressing many of the fundamental STW questions. This dissertation is to investigate and resolve a few hurdles in advancing this technology, and produce a realizable high performance STW platform system, which will aid the STW community to find the ultimate answer through experimental and theoretical work. The architectures of a realizable STW imaging system are thoroughly examined and studied. We present both a conceptual system based on RF instruments and a standalone real-time system based on custom design, which utilize reconfigurable design architecture and allows scaling down/up to a desired UWB operating frequency with little difficulty. The systems will serve as a high performance platform for STW study and other related UWB applications. Along the way to a complete STW system, we have developed a simplified transmission line model for wall characteristic prediction; we have developed a scalable synthetic aperture array including both the RF part and the switch control/synchronization part; we have proposed a cost-effective and efficient UWB data acquisition method for real-time STW application based on equivalent-time sampling method. The measurement results reported here include static image formation and tracking moveable targets behind the wall. Even though digital signal processing to generate radar images is not the focus of this research, simple methods for image formation have been implemented and results are very encouraging

Ultrasound Imaging

In this book, we present a dozen state of the art developments for ultrasound imaging, for example, hardware implementation, transducer, beamforming, signal processing, measurement of elasticity and diagnosis. The editors would like to thank all the chapter authors, who focused on the publication of this book

Sonar systems for object recognition

The deep sea exploration and exploitation is one of the biggest challenges of the next century. Military, oil & gas, o shore wind farming, underwater mining, oceanography are some of the actors interested in this eld. The engineering and technical challenges to perform any tasks underwater are great but the most crucial element in any underwater systems has to be the sensors. In air numerous sensor systems have been developed: optic cameras, laser scanner or radar systems. Unfortunately electro magnetic waves propagate poorly in water, therefore acoustic sensors are a much preferred tool then optical ones. This thesis is dedicated to the study of the present and the future of acoustic sensors for detection, identi cation or survey. We will explore several sonar con gurations and designs and their corresponding models for target scattering. We will show that object echoes can contain essential information concerning its structure and/or composition

A practical guide to photoacoustic tomography in the life sciences

The life sciences can benefit greatly from imaging technologies that connect microscopic discoveries with macroscopic observations. One technology uniquely positioned to provide such benefits is photoacoustic tomography (PAT), a sensitive modality for imaging optical absorption contrast over a range of spatial scales at high speed. In PAT, endogenous contrast reveals a tissue's anatomical, functional, metabolic, and histologic properties, and exogenous contrast provides molecular and cellular specificity. The spatial scale of PAT covers organelles, cells, tissues, organs, and small animals. Consequently, PAT is complementary to other imaging modalities in contrast mechanism, penetration, spatial resolution, and temporal resolution. We review the fundamentals of PAT and provide practical guidelines for matching PAT systems with research needs. We also summarize the most promising biomedical applications of PAT, discuss related challenges, and envision PAT's potential to lead to further breakthroughs

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

Airborne fine-resolution UHF radar: an approach to the study of englacial reflections, firn compaction and ice attenuation rates

This is the published version. Copyright 2015 International Glaciological SocietyWe have built and operated an ultra-wideband UHF pulsed-chirp radar for measuring firn stratigraphy from airborne platforms over the ice sheets of Greenland and West Antarctica. Our analysis found a wide range of capabilities, including imaging of post firn–ice transition horizons and sounding of shallow glaciers and ice shelves. Imaging of horizons to depths exceeding 600 m was possible in the colder interior regions of the ice sheet, where scattering from the ice surface and inclusions was minimal. The radar's high sensitivity and large dynamic range point to loss tangent variations as the dominant mechanism for these englacial reflective horizons. The radar is capable of mapping interfaces with reflection coefficients as low as –80 dB near the firn–ice transition and as low as –64 dB at depths of 600 m. We found that firn horizon reflectivity strongly mirrored density variance, a result of the near-unity interfacial transmission coefficients. Zones with differing compaction mechanisms were also apparent in the data. We were able to sound many ice shelves and areas of shallow ice. We estimated ice attenuation rates for a few locations, and our attenuation estimates for the Ross Ice Shelf, West Antarctica, appear to agree well with earlier reported results

Microwave Tomography Using Stochastic Optimization And High Performance Computing

This thesis discusses the application of parallel computing in microwave tomography for detection and imaging of dielectric objects. The main focus is on microwave tomography with the use of a parallelized Finite Difference Time Domain (FDTD) forward solver in conjunction with non-linear stochastic optimization based inverse solvers. Because such solvers require very heavy computation, their investigation has been limited in favour of deterministic inverse solvers that make use of assumptions and approximations of the imaging target. Without the use of linearization assumptions, a non-linear stochastic microwave tomography system is able to resolve targets of arbitrary permittivity contrast profiles while avoiding convergence to local minima of the microwave tomography optimization space. This work is focused on ameliorating this computational load with the use of heavy parallelization. The presented microwave tomography system is capable of modelling complex, heterogeneous, and dispersive media using the Debye model. A detailed explanation of the dispersive FDTD is presented herein. The system uses scattered field data due to multiple excitation angles, frequencies, and observation angles in order to improve target resolution, reduce the ill-posedness of the microwave tomography inverse problem, and improve the accuracy of the complex permittivity profile of the imaging target. The FDTD forward solver is parallelized with the use of the Common Unified Device Architecture (CUDA) programming model developed by NVIDIA corporation. In the forward solver, the time stepping of the fields are computed on a Graphics Processing Unit (GPU). In addition the inverse solver makes use of the Message Passing Interface (MPI) system to distribute computation across multiple work stations. The FDTD method was chosen due to its ease of parallelization using GPU computing, in addition to its ability to simulate wideband excitation signals during a single forward simulation. We investigated the use of distributed Particle Swarm Optimization (PSO) and Differential Evolution (DE) methods in the inverse solver for this microwave tomography system. In these optimization algorithms, candidate solutions are farmed out to separate workstations to be evaluated. As fitness evaluations are returned asynchronously, the optimization algorithm updates the population of candidate solutions and gives new candidate solutions to be evaluated to open workstations. In this manner, we used a total of eight graphics processing units during optimization with minimal downtime. Presented in this thesis is a microwave tomography algorithm that does not rely on linearization assumptions, capable of imaging a target in a reasonable amount of time for clinical applications. The proposed algorithm was tested using numerical phantoms that with material parameters similar to what one would find in normal or malignant human tissue

Enhanced microwave imaging of the subsurface for humanitarian demining applications

© Cranfield University 2020. All rights reserved. No part of this publication may be reproduced without the written permission of the copyright ownerThis thesis presents a theoretical analysis and applied evaluation deploying ground penetrating radar (GPR) for landmine detection. An original contribution has been made in designing and manufacturing a light-weight, low-cost, fully polarimetric antenna system for GPR, enabling easy transportation and assembly. This facilitates extensive use by various smaller communities in remote areas. By achieving the goal of supplying various smaller communities with advanced ground penetrating radar technology the technological standard of landmine detection can be improved beyond existing solutions such as metal detection or manual probing. The novel radar system itself allows detection of various subsurface targets of different shapes and sizes, metallic and non-metallic, in a number of different soils, such as sand, loam or gravel and therefore can be used in versatile environments. The GPR system has been realised by designing novel light-weight, 3D printed X-band horn antennas, manufactured from single piece plastic then copper electroplated. These antennas are 50% lighter than their commercial equivalents. They are incorporated in an antenna array as a group of four to allow full-polarimetric imaging of the subsurface. High resolution images of landmines and calibration targets were performed in the subsurface over an experimental sand test bed. For performing subsurface measurements in the near-field, four novel gradient-index (GRIN) lenses were designed and 3D printed to be incorporated in the apertures of the Xband antennas. The improved target detection from these lenses was proven by scanning the test bed and comparing the imaging data of the antenna array with and without lensesattached. A rigorous theoretical study of different decomposition techniques and their effect on the imaging and detection accuracy for polarimetric surface penetrating data was performed and applied to the gathered imaging data to reliably isolate and detect subsurface targets. Studied decomposition techniques were Pauli decomposition parameters and Yamaguchi polarimetry decomposition. It was found that it is paramount to use both algorithms on one set of subsurface data to detect all features of a buried target. A novel temporal imaging technique was developed for exploiting natural occurring changes in soil moisture level, and hence its dielectric properties. Contrary to the previously introduced imaging techniques this moisture change detection (MCD) mechanism does not rely on knowledge of the used measurement setup or deploying clutter suppression techniques. This time averaged technique uses several images of a moist subsurface taken over a period while the moisture evaporates from the soil. Each image pixel is weighted by the phase change occurring over the evaporation period and a resulting B-scan image reveals the subsurface targets without surrounding clutter. Finally, a multi-static antenna set-up is examined on its capability for suppressing surface clutter and its limitations are verified by introducing artificial surface clutter in form of pebbles to the scene. The resulting technique was found to suppress up to 30 The GPR antenna system developed in this thesis and the corresponding imaging techniques have contributed to a significant improvement in subsurface radar imaging performance and target discrimination capabilities. This work will contribute to more efficient landmine clearance in some of the most challenged parts of the world