[en] Indoor location has experienced a major boost in recent years. location based services (LBS), which until recently were restricted to outdoor scenarios and the use of GPS, have also been extended into buildings. From large public structures such as airports or hospitals to a multitude of industrial scenarios, LBS has become increasingly present in indoor scenarios. Of the various technologies that can be used to achieve this indoor location, the ones based on ultrawideband (UWB) signals have become ones of the most demanded due primarily to their accuracy in position estimation. Additionally, the appearance in the market of more and more manufacturers and products has lowered the prices of these devices to levels that allow to think about their use for large deployments with a contained budget. By their nature, UWB signals are very resistant to the multi-path phenomenon, so in a situation of good direct vision between two devices (line-of-sight (LOS)) the technology is able to provide very accurate distance estimates. This is not the case when this line of sight is totally or partially blocked (non-line-of-sight (NLOS)). In this case the possible rebounds of the signal can be wrongly confused with the original emitted signal and result in an estimate of time, and therefore distance, very far from the actual value. The aim of this thesis is to offer a complete solution to the problem of indoor location with UWB from a practical approach. This means that the problem is approached from all the angles that should be taken into account in a real use case: basic research in search of an improvement at technical level of the UWB values, prior simulation to ensure a good deployment and performance and the final integration of the solution within an external operational system that allows LBS or clients to make use of location data. The first part of this proposal is presented in this thesis in the first chapters, and consists of using machine learning (ML) techniques to detect and mitigate the possible NLOS measurements generated by low-cost UWB devices. For this task the memory describes the different measurement campaigns with real hardware that were carried out to obtain the training data of the algorithms, and how these were used in different experiments to measure to what extent the proposed solution was valid in a real environment. The second part of the thesis presents data from a location-oriented UWB devices simulator created to perform tests and detect possible problems before deploying real hardware. Among the data presented during this second part, different comparisons between real and simulated scenarios are shown in order to check how reliable the simulation is. In addition, the simulator is presented as part of a case commonly used in indoor location systems: the location of vehicles in an industrial environment using multiple sensors. Finally, the third and final part of this thesis describes a multi-technology real-time location system (RTLS) capable of serving the different actors in a real location system. The platform serves as a link between the location sensors themselves, the LBS and end clients, the researchers in charge of the location algorithms and the managers of derived services such as alerts. By means of the proposed RTLS platform it is possible to decouple the functionality of these entities so that all of them can work without dependencies with the others. In addition to the description of the platform, this memory also includes a summary of the real localization projects in which it has been used, as well as a list of the various modifications and improvements that the platform has undergone in recent times thanks exactly to the experiences obtained after those works on site with real projects.

[gl] A localización en interiores sufriu dun importante empuxe nos últimos anos. Os servizos baseados en localización (location based services (LBS)) que ata fai pouco estaban restrinxidos a escenarios exteriores e a o uso do GPS, foron estendéndose tamén cara o interior dos edificios. Dende grandes estruturas públicas como aeroportos ou hospitais ata multitude de escenarios industriais, os LBS están cada vez mais presentes baixo teito. De entre as diversas tecnoloxías que poden ser utilizadas para acadar esta localización en interiores, as baseadas en sinais ultra-wideband (UWB) convertéronse nunha das mais demandadas debido fundamentalmente á súa precisión na estimación de posición. Adicionalmente, a aparición no mercado de cada vez mais fabricantes e mais produtos fixo diminuír os prezos destes dispositivos ata niveis que permiten pensar no seu uso para grandes despregues con un presuposto contido. Pola súa natureza, os sinais UWB son moi resistentes ao fenómeno de multi-traxecto, polo que nunha situación de boa visión directa entre os dous dispositivos (LOS) a tecnoloxía é capaz de proporcionar estimación de distancia moi precisas. Isto non ocorre así cando esta liña de de visión está total ou parcialmente bloqueada (NLOS). Neste caso os posibles rebotes do sinal poden ser erroneamente confundidos co sinal orixinal e derivar nunha estimación de tempo, e por tanto distancia, moi alonxada do seu valor real. O obxectivo desta tese é o de ofrecer una solución completa ao problema da localización en interiores con UWB dende un enfoque práctico. Isto quere dicir que se aborda o problema dende todos os ángulos que se deberían ter en conta nun caso de uso real: a investigación básica en busca dunha mellora a nivel técnico dos valores de UWB, a simulación previa para garantir un bo despregue e rendemento e a integración final da solución dentro dunha operativa externa que permita a LBS ou clientes poder facer uso dos datos de localización. A primeira parte desta proposta presentase nos primeiros capítulos da tese, e consiste en utilizar algoritmos de aprendizaxe automático (machine learning (ML)) para detectar e mitigar as posibles medidas NLOS xeradas por dispositivos UWB de baixo custo. Para esta tarefa móstranse as diferentes campañas de medida con dispositivos reais que se realizaron para obter os datos de adestramento dos algoritmos, e como estes se empregaron en diferentes experimentos para medir ata que punto a solución proposta era válida nun entorno real. A segunda parte da tese presenta pola súa parte os datos dun simulador de dispositivos UWB orientado á localización creado para poder realizar probas e detectar posibles problemas antes de efectuar un despregue con dispositivos reais. Entre os datos presentados durante esta segunda parte móstranse diferentes comparativas entre escenarios reais e simulados para comprobar como de fidedigna é a simulación. Ademais, preséntase o simulador integrado dentro dun caso de uso habitual nos sistema de localización en interiores: a localización de vehículos nun entorno industrial utilizando múltiples sensores. Por último, a terceira e derradeira parte desta tese describe unha plataforma de localización en tempo real (real-time location system (RTLS)) multi-tecnoloxía capaz de dar servizo aos diferentes actores habituais nun sistema de localización real. A plataforma serve de punto de unión entre os propios sensores de localización, os LBS e clientes finais, os investigadores encargados da algorítmica de localización e os xestores de servizos derivados como alertas. Mediante a plataforma RTLS proposta nesta terceira parte da memoria lograse desacoplar a funcionalidade destas entidades de forma que todas elas poden traballar sen depender das demais. Ademais da descrición da plataforma, inclúese tamén un resumo dos proxectos reais de localización nos que esta foi utilizada, así como un listado das diversas modificación e melloras que a plataforma sufriu nos últimos tempos grazas precisamente as experiencias obtidas tras estes traballos sobre o terreo con proxectos reais.