Development and Experimental Analysis of Wireless High Accuracy Ultra-Wideband Localization Systems for Indoor Medical Applications

This dissertation addresses several interesting and relevant problems in the field of wireless technologies applied to medical applications and specifically problems related to ultra-wideband high accuracy localization for use in the operating room. This research is cross disciplinary in nature and fundamentally builds upon microwave engineering, software engineering, systems engineering, and biomedical engineering. A good portion of this work has been published in peer reviewed microwave engineering and biomedical engineering conferences and journals. Wireless technologies in medicine are discussed with focus on ultra-wideband positioning in orthopedic surgical navigation. Characterization of the operating room as a medium for ultra-wideband signal transmission helps define system design requirements. A discussion of the first generation positioning system provides a context for understanding the overall system architecture of the second generation ultra-wideband positioning system outlined in this dissertation. A system-level simulation framework provides a method for rapid prototyping of ultra-wideband positioning systems which takes into account all facets of the system (analog, digital, channel, experimental setup). This provides a robust framework for optimizing overall system design in realistic propagation environments. A practical approach is taken to outline the development of the second generation ultra-wideband positioning system which includes an integrated tag design and real-time dynamic tracking of multiple tags. The tag and receiver designs are outlined as well as receiver-side digital signal processing, system-level design support for multi-tag tracking, and potential error sources observed in dynamic experiments including phase center error, clock jitter and drift, and geometric position dilution of precision. An experimental analysis of the multi-tag positioning system provides insight into overall system performance including the main sources of error. A five base station experiment shows the potential of redundant base stations in improving overall dynamic accuracy. Finally, the system performance in low signal-to-noise ratio and non-line-of-sight environments is analyzed by focusing on receiver-side digitally-implemented ranging algorithms including leading-edge detection and peak detection. These technologies are aimed at use in next-generation medical systems with many applications including surgical navigation, wireless telemetry, medical asset tracking, and in vivo wireless sensors

Evaluation and Comparison of Ultrasonic and UWB Technology for Indoor Localization in an Industrial Environment

Evaluations of different technologies and solutions for indoor localization exist but only a few are aimed at the industrial context. In this paper, we compare and analyze two prominent solutions based on Ultra Wide Band Radio (Pozyx) and Ultrasound (GoT), both installed in an industrial manufacturing laboratory. The comparison comprises a static and a dynamic case. The static case evaluates average localization errors over 90 s intervals for 100 ground-truth points at three different heights, corresponding to different relevant objects in an industrial environment: mobile robots, pallets, forklifts and worker helmets. The average error obtained across the laboratory is similar for both systems and is between 0.3 m and 0.6 m, with higher errors for low altitudes. The dynamic case is performed with a mobile robot travelling with an average speed of 0.5 m/s at a height of 0.3 m. In this case, low frequency error components are filtered out to focus the comparison on dynamic errors. Average dynamic errors are within 0.3–0.4 m for Pozyx and within 0.1–0.2 m for GoT. Results show an acceptable accuracy required for tracking people or objects and could serve as a guideline for the least achievable accuracy when applied for mobile robotics in conjunction with other elements of a robotic navigation stack

Ultra-wideband systems exploiting orthonormal waveforms

textElectrical and Computer Engineerin

Position estimation for IR-UWB systems using compressive sensing

One major challenge in IR-UWB signal processing is the requirement of high sampling rate, which renders standard analog-to-digital converter (ADC) costly and even impractical. Compressive Sensing (CS) provides a solution to this problem by allowing to sample UWB signals at a rate significantly lesser than the Nyquist sampling limit.Ultra-Wideband (UWB) technology, thanks to its high time resolution, arises as an excellent candidate to provide accurate positioning information in cluttered environments. However, the dense multipath and strong attenuation of the Line-of-Sight (LOS) present in UWB channels poses additional challenges to positioning algorithms. Therefore, in this thesis we have mainly focused on designing an algorithm robust to these problems. Specifically, we have developed two different techniques based on a frequency domain receiver. The first one is based on a Direct Position Estimation (DPE) approach, that is, estimating the position directly from the observed signals, while the second is based on ?soft? two-steps approach, where more than one estimated Time of Arrival (TOA) is estimated on each anchor, then in the second stage the best estimators are used to find the position. Simulation results proof the accuracy of the proposed algorithms. Besides, the proposed methods have also been tested while using Compressive Sensing (CS). CS is a new sensing paradigm that allows compressing signals while they are being sampled, thus it allows to sample at a lower rather than the Nyquist limit.La tecnología Ultra-Wideband (UWB), gracias a su alta resolución temporal, se presenta como un candidato ideal per proporcionar información de la posición precisa en ambientes muy densos. Sin embargo, la gran concentración de propagación multi camino, así como la fuerte atenuación del camino de visión directa (LOS) característica de los canales UWB conlleva grandes dificultades a la hora de estimar la posición. Por esta razón, en esta tesis nos hemos centrado principalmente en diseñar algoritmos robustos a la problemática que presenten los canales UWB. Concretamente, hemos desarrollado dos técnicas basadas en un receptor en el dominio de la frecuencia. La primera está basada en una estimación directa de la posición (DPE) a partir de las señales recibidas, mientras que la segunda está basada en una estimación en dos etapas pero con la diferencia que en la primera etapa se proporcionen diversos estimadores del tiempo de vuelo (TOA) y en la segunda se seleccionen los mejores estimadores para estimar la posición. Los resultados de les simulaciones demuestran la precisión del los algoritmos propuestos. Además, los métodos propuestos también se han probado utilizando Compressive Sensing (CS). El CS es un nuevo paradigma en la teoría del muestreo que permite comprimir una señal al mismo tiempo que se está muestreando, permitiendo así muestrear per debajo del límite de Nyquist.La tecnologia Ultra-Wideband (UWB), gràcies a la seva alta resolució temporal, es presenta com un candidat ideal per proporcionar informació de la posició precisa en ambients molt densos. Tanmateix, la gran concentració de propagació multi camí, així com la forta atenuació del camí de visió directa (LOS) característica del canals UWB comporta grans dificultats a l?hora d?estimar la posició. Per aquesta raó, en aquesta tesis ens hem centrat principalment en dissenyar algoritmes robusts a la problemàtica que presenten els canals UWB. Concretament, hem desenvolupat dues tècniques basades en un receptor en el domini freqüencial. La primera està basada en una estimació directa de la posició (DPE) a partir dels senyals rebuts, mentre que la segona està basada en una estimació en dues etapes però amb la diferència que en la primera etapa es proporcionen diversos estimadors del temps de vol (TOA) i en la segona es seleccionen els millors estimadors per trobar la posició. Els resultats de les simulacions demostren la precisió dels algoritmes proposats. A més a més, els mètodes proposats també s?han provat fent servir Compressive Sensing (CS). CS és un nou paradigma en la teoria del mostreig que permet comprimir una senyal mentre s?està mostrejant, permetent així mostrejar per sota del límit de Nyquist