The Future of the Operating Room: Surgical Preplanning and Navigation using High Accuracy Ultra-Wideband Positioning and Advanced Bone Measurement

This dissertation embodies the diversity and creativity of my research, of which much has been peer-reviewed, published in archival quality journals, and presented nationally and internationally. Portions of the work described herein have been published in the fields of image processing, forensic anthropology, physical anthropology, biomedical engineering, clinical orthopedics, and microwave engineering. The problem studied is primarily that of developing the tools and technologies for a next-generation surgical navigation system. The discussion focuses on the underlying technologies of a novel microwave positioning subsystem and a bone analysis subsystem. The methodologies behind each of these technologies are presented in the context of the overall system with the salient results helping to elucidate the difficult facets of the problem. The microwave positioning system is currently the highest accuracy wireless ultra-wideband positioning system that can be found in the literature. The challenges in producing a system with these capabilities are many, and the research and development in solving these problems should further the art of high accuracy pulse-based positioning

Hardware Development of an Ultra-Wideband System for High Precision Localization Applications

A precise localization system in an indoor environment has been developed. The developed system is based on transmitting and receiving picosecond pulses and carrying out a complete narrow-pulse, signal detection and processing scheme in the time domain. The challenges in developing such a system include: generating ultra wideband (UWB) pulses, pulse dispersion due to antennas, modeling of complex propagation channels with severe multipath effects, need for extremely high sampling rates for digital processing, synchronization between the tag and receivers’ clocks, clock jitter, local oscillator (LO) phase noise, frequency offset between tag and receivers’ LOs, and antenna phase center variation. For such a high precision system with mm or even sub-mm accuracy, all these effects should be accounted for and minimized. In this work, we have successfully addressed many of the above challenges and developed a stand-alone system for positioning both static and dynamic targets with approximately 2 mm and 6 mm of 3-D accuracy, respectively. The results have exceeded the state of the art for any commercially available UWB positioning system and are considered a great milestone in developing such technology. My contributions include the development of a picosecond pulse generator, an extremely wideband omni-directional antenna, a highly directive UWB receiving antenna with low phase center variation, an extremely high data rate sampler, and establishment of a non-synchronized UWB system architecture. The developed low cost sampler, for example, can be easily utilized to sample narrow pulses with up to 1000 GS/s while the developed antennas can cover over 6 GHz bandwidth with minimal pulse distortion. The stand-alone prototype system is based on tracking a target using 4-6 base stations and utilizing a triangulation scheme to find its location in space. Advanced signal processing algorithms based on first peak and leading edge detection have been developed and extensively evaluated to achieve high accuracy 3-D localization. 1D, 2D and 3D experiments have been carried out and validated using an optical reference system which provides better than 0.3 mm 3-D accuracy. Such a high accuracy wireless localization system should have a great impact on the operating room of the future

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

Hybrid AOA and TDOA Solution for Transmitter Positioning

Accurate positioning has become an active research area in recent years. It has a wide range of applications in many fields such as navigation, asset tracking, health care, proximity marketing/location-based advertising, and sport analytics. Transmitter positioning via radio frequency (RF) signals is the most widely encountered scenario, and it uses a two-step process: First, parameters that depend on the location of the transmitter are extracted from the received signal. Second, the transmitter’s location is estimated by using these parameters. Many parameters can be used; for instance, time of arrival (TOA), time difference of arrival (TDOA), angle of arrival (AOA), and received signal strength (RSS). Localization can use one or multiple of such parameters. In this thesis, a hybrid AOA and TDOA method is studied. Specifically, an array of N collinear receiving antennas are employed to estimate the transmitter position. In order to use AOA, existing assumes that the transmitter is far away from the receiving antennas and that the spacing between the receiving antennas is very small (typically a fraction of one wavelength). This ensures that the directions of the incident waves to all receivers are parallel, so that there is a single AOA for all receivers. Such condition cannot be maintained for some scenarios (e.g., when wavelength is very large). Also, in order to use valid TDOAs, the receiving antennas cannot be placed very close to one another, which will result a unique AOA for each of the receiving antennas. This research develop solutions for the cases where the above constraints cannot be maintained. A maximum likelihood (ML) estimator is developed to obtain the AOA of each receiving antenna assuming there is no limitation on the antenna spacing; it can be sufficiently large orsmall . A cross correlation algorithm is used to determine the TDOA between the received signals. Finally, an algorithm that jointly processes the AOAs and the TDOAs to estimate the position of the transmitter is developed

Target Localization Using Approximate Maximum Likelihood for MIMO Radar Systems

This thesis deals with target localization using multiple-input multiple-output (MIMO) radars. In the field of communications, navigation, radar, and sensing networks, one of the common and most sophisticated problems is target localization. We develop a target localization scheme in distributed MIMO radar systems using bistatic range measurements. The localization approach consists of two phases. First, measurements are divided into multiple groups based on the various transmitter and receiver elements. For each group, an approximate maximum likelihood (AML) estimator is proposed to estimate the location of a target. Then, the estimation results from these different groups are combined to form the final estimate. The performance of the proposed algorithm is validated by simulation and is shown to reach the Cram\'{e}r-Rao lower bound (CRLB) in a range of measurement noise levels. The main advantage of the proposed algorithm is that it achieves a higher accuracy than existing schemes for locating a target position in high-noise conditions

A Novel CCRW Receiver with Variable Width Window for Mitigating Multipath and Ambiguity in GNSS Positioning

This work presents a novel CCRW receiver that utilizes a window of variable width, for e˙ectively mitigating multipath and ambiguity in both civil and military positioning applica-tions using Global Navigation Satellite Systems (GNSS). This CCRW receiver incorporates a single stroboscopic window, whose width is iteratively reduced until the e˙ect of multipath is mitigated. Results show that this receiver is very e˙ective reduces the e˙ects of multipath of any delay, thus outperforming the fixed window width counterparts which exhibit rather large errors for multipath of small delays. The receiver also demonstrated its capability of mitigating the ambiguity that appears when MBOC modulations are used in receivers designed to work with BOC modulations. In addition, it is computationally simple, and therefore suitable for implementation in low-cost GNSS commercial receivers

Cognitive radar network design and applications

PhD ThesisIn recent years, several emerging technologies in modern radar system design are attracting the attention of radar researchers and practitioners alike, noteworthy among which are multiple-input multiple-output (MIMO), ultra wideband (UWB) and joint communication-radar technologies. This thesis, in particular focuses upon a cognitive approach to design these modern radars. In the existing literature, these technologies have been implemented on a traditional platform in which the transmitter and receiver subsystems are discrete and do not exchange vital radar scene information. Although such radar architectures benefit from these mentioned technological advances, their performance remains sub-optimal due to the lack of exchange of dynamic radar scene information between the subsystems. Consequently, such systems are not capable to adapt their operational parameters “on the fly”, which is in accordance with the dynamic radar environment. This thesis explores the research gap of evaluating cognitive mechanisms, which could enable modern radars to adapt their operational parameters like waveform, power and spectrum by continually learning about the radar scene through constant interactions with the environment and exchanging this information between the radar transmitter and receiver. The cognitive feedback between the receiver and transmitter subsystems is the facilitator of intelligence for this type of architecture. In this thesis, the cognitive architecture is fused together with modern radar systems like MIMO, UWB and joint communication-radar designs to achieve significant performance improvement in terms of target parameter extraction. Specifically, in the context of MIMO radar, a novel cognitive waveform optimization approach has been developed which facilitates enhanced target signature extraction. In terms of UWB radar system design, a novel cognitive illumination and target tracking algorithm for target parameter extraction in indoor scenarios has been developed. A cognitive system architecture and waveform design algorithm has been proposed for joint communication-radar systems. This thesis also explores the development of cognitive dynamic systems that allows the fusion of cognitive radar and cognitive radio paradigms for optimal resources allocation in wireless networks. In summary, the thesis provides a theoretical framework for implementing cognitive mechanisms in modern radar system design. Through such a novel approach, intelligent illumination strategies could be devised, which enable the adaptation of radar operational modes in accordance with the target scene variations in real time. This leads to the development of radar systems which are better aware of their surroundings and are able to quickly adapt to the target scene variations in real time.Newcastle University, Newcastle upon Tyne: University of Greenwich

Environment-adaptive RF Sensing with Transferable ANN Features

Radio frequency (RF) sensing arises as a promising option for enabling the internet of things (IoT) applications that transform our life into a world of smart homes, smart cities, and smart industries. The innovation of IoT reveals the benefits of RF sensing across cost, pervasiveness, unobtrusiveness, and privacy. However, challenges like interference and multipath are underway in realizing those promises. Furthermore, crucial studies demonstrate the trade-offs in accuracy, accessibility, power consumption, and many other factors for undertaking RF sensing. This dissertation presents a set of studies, including RF channel model characterization, the design of a novel RF sensing system for indoor localization, and the environmental impact of RF exposure in such systems. The first part covers a use case of measurement-based RF channel modeling in a challenging environment. The second part introduces an environment-adaptive RF sensing system for indoor localization that consists of 1) a dynamic phase calibration de-noising method, and 2) The implementation of a localization system that utilizes an artificial neural network (ANN) with transferable features. Lastly, a collaboration work that explores the potential impact of RF radiation and how RF exposure could affect human health