257 research outputs found
A Survey of Positioning Systems Using Visible LED Lights
© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.As Global Positioning System (GPS) cannot provide satisfying performance in indoor environments, indoor positioning technology, which utilizes indoor wireless signals instead of GPS signals, has grown rapidly in recent years. Meanwhile, visible light communication (VLC) using light devices such as light emitting diodes (LEDs) has been deemed to be a promising candidate in the heterogeneous wireless networks that may collaborate with radio frequencies (RF) wireless networks. In particular, light-fidelity has a great potential for deployment in future indoor environments because of its high throughput and security advantages. This paper provides a comprehensive study of a novel positioning technology based on visible white LED lights, which has attracted much attention from both academia and industry. The essential characteristics and principles of this system are deeply discussed, and relevant positioning algorithms and designs are classified and elaborated. This paper undertakes a thorough investigation into current LED-based indoor positioning systems and compares their performance through many aspects, such as test environment, accuracy, and cost. It presents indoor hybrid positioning systems among VLC and other systems (e.g., inertial sensors and RF systems). We also review and classify outdoor VLC positioning applications for the first time. Finally, this paper surveys major advances as well as open issues, challenges, and future research directions in VLC positioning systems.Peer reviewe
Device-free indoor localisation with non-wireless sensing techniques : a thesis by publications presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Electronics and Computer Engineering, Massey University, Albany, New Zealand
Global Navigation Satellite Systems provide accurate and reliable outdoor positioning to support a large number of applications across many sectors. Unfortunately, such systems do not operate reliably inside buildings due to the signal degradation caused by the absence of a clear line of sight with the satellites. The past two decades have therefore seen intensive research into the development of Indoor Positioning System (IPS). While considerable progress has been made in the indoor localisation discipline, there is still no widely adopted solution. The proliferation of Internet of Things (IoT) devices within the modern built environment provides an opportunity to localise human subjects by utilising such ubiquitous networked devices. This thesis presents the development, implementation and evaluation of several passive indoor positioning systems using ambient Visible Light Positioning (VLP), capacitive-flooring, and thermopile sensors (low-resolution thermal cameras). These systems position the human subject in a device-free manner (i.e., the subject is not required to be instrumented). The developed systems improve upon the state-of-the-art solutions by offering superior position accuracy whilst also using more robust and generalised test setups. The developed passive VLP system is one of the first reported solutions making use of ambient light to position a moving human subject. The capacitive-floor based system improves upon the accuracy of existing flooring solutions as well as demonstrates the potential for automated fall detection. The system also requires very little calibration, i.e., variations of the environment or subject have very little impact upon it. The thermopile positioning system is also shown to be robust to changes in the environment and subjects. Improvements are made over the current literature by testing across multiple environments and subjects whilst using a robust ground truth system. Finally, advanced machine learning methods were implemented and benchmarked against a thermopile dataset which has been made available for other researchers to use
On Proximity Based Sub-Area Localization
A localization system can save lives in the aftermath of an earthquake; position people or valuable assets during a fire in a building; or track airplanes besides many of its other attractive applications. Global Positioning System (GPS) is the most popular localization system, and it can provide 7-10 meters localization accuracy for outdoor users; however, it has certain drawbacks for indoor environments. Alternatively, wireless networks are becoming pervasive and have been densely deployed for communication of various types of devices indoors, exploiting them for the localization of people or other assets is a convenience. Proximity based localization that estimates locations based on closeness to known reference points, coupled with a widely deployed wireless technology, can reduce the cost and effort for localization in local and indoor areas. In this dissertation, we propose a proximity based localization algorithm that exploits knowledge of the overlapping coverages of known monitoring stations. We call this algorithm Sub-Area Localization (SAL). We present a systematic study of proximity-based localization by defining the factors and parameters that affect the localization performance in terms of metrics such as accuracy and efficiency. Then, we demonstrate that SAL can be used in multi-floor buildings to take advantage of the infrastructure elements deployed across floors to reduce the overall cost (in terms of the number of monitoring stations required) without harming accuracy. Finally, we present a case study of how SAL can be used for spatial spectrum detection in wireless cognitive networks
Systèmes de localisation en temps réel basés sur les réseaux de communication sans fil
Des techniques fiables de radiolocalisation s’avèrent indispensables au développement d’un grand nombre de nouveaux systèmes pertinents. Les techniques de localisation basées sur les réseaux de communication sans-fil (WNs) sont particulièrement adéquates aux espaces confinés et fortement urbanisés. Le présent projet de recherche s’intéresse aux systèmes de localisation en temps réel (RTLS) basés sur les technologies de communication sans-fil existantes. Deux nouvelles techniques de radiolocalisation alternatives sont proposées pour améliorer la précision de positionnement des nœuds sans-fil mobiles par rapport aux méthodes conventionnelles basées sur la puissance des signaux reçus (RSS). La première méthode de type géométrique propose une nouvelle métrique de compensation entre les puissances de signaux reçus par rapport à des paires de stations réceptrices fixes. L’avantage de cette technique est de réduire l’effet des variations du milieu de propagation et des puissances d’émission des signaux sur la précision de localisation. La même métrique est sélectionnée pour former les signatures utilisées pour créer la carte radio de l’environnement de localisation durant la phase hors-ligne dans la deuxième méthode de type analyse de situation. Durant la phase de localisation en temps réel, la technique d’acquisition comprimée (CS) est appliquée pour retrouver les positions des nœuds mobiles à partir d’un nombre réduit d’échantillons de signaux reçus en les comparant à la carte radio préétablie. Le calcul d’algèbre multilinéaire proposé dans ce travail permet l’utilisation de ce type de métrique ternaire, équivalemment la différence des temps d’arrivée (TDOA), pour calculer les positions des cibles selon la technique de CS. Les deux méthodes sont ensuite validées par des simulations et des expérimentations effectuées dans des environnements à deux et à trois dimensions. Les expériences ont été menées dans un bâtiment multi-étages (MFB) en utilisant l’infrastructure sans-fil existante pour retrouver conjointement la position et l’étage des cibles en utilisant les techniques proposées. Un exemple emblématique de l’application des RTLS dans les zones urbaines est celui des systèmes de transport intelligents (ITS) pour améliorer la sécurité routière. Ce projet s’intéresse également à la performance d’une application de sécurité des piétons au niveau des intersections routières. L’accomplissement d’un tel système repose sur l’échange fiable, sous des contraintes temporelles sévères, des données de positionnement géographique entre nœuds mobiles pour se tenir mutuellement informés de leurs présences et positions afin de prévenir les risques de collision. Ce projet mène une étude comparative entre deux architectures d’un système ITS permettant la communication entre piétons et véhicules, directement et via une unité de l’infrastructure, conformément aux standards de communication dans les réseaux ad hoc véhiculaires (VANETs)
Effiziente Lokalisierung von Nutzern und Geräten in Smarten Umgebungen
The thesis considers determination of location of sensors and users in smart environments using measurements of Received Signal Strength (RSS). The first part of the thesis focuses on localization in Wireless Sensor Networks and contributes two fully distributed algorithms which address the Sensor Selection Problem and provide the best trade-off between energy consumption and localization accuracy among the algorithms considered. Furthermore, the thesis contributes to Device Free Localization an indoor localization concept providing scalable and highly accurate location estimates (prototype: 0.36m² MSE) while using a COTS passive RFID-System and not relying on user-carried sensors
Sistemas de posicionamento baseados em comunicação por luz para ambientes interiores
The demand for highly precise indoor positioning systems (IPSs) is growing
rapidly due to its potential in the increasingly popular techniques of the
Internet of Things, smart mobile devices, and artificial intelligence. IPS
becomes a promising research domain that is getting wide attention due to its
benefits in several working scenarios, such as, industries, indoor public
locations, and autonomous navigation. Moreover, IPS has a prominent
contribution in day-to-day activities in organizations such as health care
centers, airports, shopping malls, manufacturing, underground locations, etc.,
for safe operating environments. In indoor environments, both radio frequency
(RF) and optical wireless communication (OWC) based technologies could be
adopted for localization. Although the RF-based global positioning system,
such as, Global positioning system offers higher penetration rates with
reduced accuracy (i.e., in the range of a few meters), it does not work well in
indoor environments (and not at all in certain cases such as tunnels, mines,
etc.) due to the very weak signal and no direct access to the satellites. On the
other hand, the light-based system known as a visible light positioning (VLP)
system, as part of the OWC systems, uses the pre-existing light-emitting
diodes (LEDs)-based lighting infrastructure, could be used at low cost and
high accuracy compared with the RF-based systems. VLP is an emerging
technology promising high accuracy, high security, low deployment cost,
shorter time response, and low relative complexity when compared with RFbased
positioning.
However, in indoor VLP systems, there are some concerns such as,
multipath reflection, transmitter tilting, transmitter’s position, and orientation
uncertainty, human shadowing/blocking, and noise causing the increase in
the positioning error, thereby reducing the positioning accuracy of the system.
Therefore, it is imperative to capture the characteristics of different VLP
channel and properly model them for the dual purpose of illumination and
localization. In this thesis, firstly, the impact of transmitter tilting angles and
multipath reflections are studied and for the first time, it is demonstrated that
tilting the transmitter can be beneficial in VLP systems considering both line of
sight (LOS) and non-line of sight transmission paths. With the transmitters
oriented towards the center of the receiving plane, the received power level is
maximized due to the LOS components. It is also shown that the proposed
scheme offers a significant accuracy improvement of up to ~66% compared
with a typical non-tilted transmitter VLP. The effect of tilting the transmitter on
the lighting uniformity is also investigated and results proved that the
uniformity achieved complies with the European Standard EN 12464-1.
After that, the impact of transmitter position and orientation uncertainty on
the accuracy of the VLP system based on the received signal strength (RSS)
is investigated. Simulation results show that the transmitter uncertainties have
a severe impact on the positioning error, which can be leveraged through the
usage of more transmitters. Concerning a smaller transmitter’s position
epochs, and the size of the training set. It is shown that,
the ANN with Bayesian regularization outperforms the traditional RSS
technique using the non-linear least square estimation for all values of signal
to noise ratio.
Furthermore, a novel indoor VLP system is proposed based on support
vector machines and polynomial regression considering two different
multipath environments of an empty room and a furnished room. The results
show that, in an empty room, the positioning accuracy improvement for the
positioning error of 2.5 cm are 36.1, 58.3, and 72.2 % for three different
scenarios according to the regions’ distribution in the room. For the furnished
room, a positioning relative accuracy improvement of 214, 170, and 100 % is
observed for positioning error of 0.1, 0.2, and 0.3 m, respectively. Ultimately,
an indoor VLP system based on convolutional neural networks (CNN) is
proposed and demonstrated experimentally in which LEDs are used as
transmitters and a rolling shutter camera is used as receiver. A detection
algorithm named single shot detector (SSD) is used which relies on CNN (i.e.,
MobileNet or ResNet) for classification as well as position estimation of each
LED in the image. The system is validated using a real-world size test setup
containing eight LED luminaries. The obtained results show that the maximum
average root mean square positioning error achieved is 4.67 and 5.27 cm with
SSD MobileNet and SSD ResNet models, respectively. The validation results
show that the system can process 67 images per second, allowing real-time
positioning.A procura por sistemas de posicionamento interior (IPSs) de alta precisĂŁo tem
crescido rapidamente devido ao seu interesse nas técnicas cada vez mais
populares da Internet das Coisas, dispositivos mĂłveis inteligentes e
inteligĂŞncia artificial. O IPS tornou-se um domĂnio de pesquisa promissor que
tem atraĂdo grande atenção devido aos seus benefĂcios em vários cenários de
trabalho, como indústrias, locais públicos e navegação autónoma. Além disso,
o IPS tem uma contribuição destacada no dia a dia de organizações, como,
centros de saúde, aeroportos, supermercados, fábricas, locais subterrâneos,
etc. As tecnologias baseadas em radiofrequência (RF) e comunicação óptica
sem fio (OWC) podem ser adotadas para localização em ambientes interiores.
Embora o sistema de posicionamento global (GPS) baseado em RF ofereça
taxas de penetração mais altas com precisão reduzida (ou seja, na faixa de
alguns metros), nĂŁo funciona bem em ambientes interiores (e nĂŁo funciona
bem em certos casos como tĂşneis, minas, etc.) devido ao sinal muito fraco e
falta de acesso direto aos satélites. Por outro lado, o sistema baseado em luz
conhecido como sistema de posicionamento de luz visĂvel (VLP), como parte
dos sistemas OWC, usa a infraestrutura de iluminação baseada em dĂodos
emissores de luz (LEDs) pré-existentes, é um sistemas de baixo custo e alta
precisĂŁo quando comprado com os sistemas baseados em RF. O VLP Ă© uma
tecnologia emergente que promete alta precisão, alta segurança, baixo custo
de implantação, menor tempo de resposta e baixa complexidade relativa
quando comparado ao posicionamento baseado em RF.
No entanto, os sistemas VLP interiores, exibem algumas limitações, como, a
reflexão multicaminho, inclinação do transmissor, posição do transmissor e
incerteza de orientação, sombra/bloqueio humano e ruĂdo, que tĂŞm como
consequência o aumento do erro de posicionamento, e consequente redução
da precisĂŁo do sistema. Portanto, Ă© imperativo estudar as caracterĂsticas dos
diferentes canais VLP e modelá-los adequadamente para o duplo propósito de
iluminação e localização. Esta tesa aborda, primeiramente, o impacto dos
ângulos de inclinação do transmissor e reflexões multipercurso no
desempenho do sistema de posicionamento. Demonstra-se que a inclinação
do transmissor pode ser benéfica em sistemas VLP considerando tanto a linha
de vista (LOS) como as reflexões. Com os transmissores orientados para o
centro do plano recetor, o nĂvel de potĂŞncia recebido Ă© maximizado devido aos
componentes LOS. Também é mostrado que o esquema proposto oferece
uma melhoria significativa de precisão de até ~66% em comparação com um
sistema VLP de transmissor nĂŁo inclinado tĂpico. O efeito da inclinação do
transmissor na uniformidade da iluminação também é investigado e os
resultados comprovam que a uniformidade alcançada está de acordo com a
Norma Europeia EN 12464-1.
O impacto da posição do transmissor e incerteza de orientação na precisão
do sistema VLP com base na intensidade do sinal recebido (RSS) foi também investigado. Os resultados da simulação mostram que as incertezas do
transmissor tĂŞm um impacto severo no erro de posicionamento, que pode ser
atenuado com o uso de mais transmissores. Para incertezas de
posicionamento dos transmissores menores que 5 cm, os erros médios de
posicionamento sĂŁo 23.3, 15.1 e 13.2 cm para conjuntos de 4, 9 e 16
transmissores, respetivamente. Enquanto que, para a incerteza de orientação
de um transmissor menor de 5°, os erros médios de posicionamento são 31.9,
20.6 e 17 cm para conjuntos de 4, 9 e 16 transmissores, respetivamente.
O trabalho da tese abordou a investigação dos aspetos de projeto de um
sistema VLP indoor no qual uma rede neuronal artificial (ANN) Ă© utilizada para
estimativa de posicionamento considerando um canal multipercurso. O estudo
considerou a influĂŞncia do ruĂdo como indicador de desempenho para a
comparação entre diferentes abordagens de projeto. Três algoritmos de treino
de ANNs diferentes foram considerados, a saber, Levenberg-Marquardt,
regularização Bayesiana e algoritmos de gradiente conjugado escalonado,
para minimizar o erro de posicionamento no sistema VLP. O projeto da ANN foi
otimizado com base no nĂşmero de neurĂłnios nas camadas ocultas, no nĂşmero
de Ă©pocas de treino e no tamanho do conjunto de treino. Mostrou-se que, a
ANN com regularização Bayesiana superou a técnica RSS tradicional usando
a estimação nĂŁo linear dos mĂnimos quadrados para todos os valores da
relação sinal-ruĂdo.
Foi proposto um novo sistema VLP indoor baseado em máquinas de vetores
de suporte (SVM) e regressĂŁo polinomial considerando dois ambientes
interiores diferentes: uma sala vazia e uma sala mobiliada. Os resultados
mostraram que, numa sala vazia, a melhoria da precisĂŁo de posicionamento
para o erro de posicionamento de 2.5 cm sĂŁo 36.1, 58.3 e 72.2% para trĂŞs
cenários diferentes de acordo com a distribuição das regiões na sala. Para a
sala mobiliada, uma melhoria de precisĂŁo relativa de posicionamento de 214,
170 e 100% Ă© observada para erro de posicionamento de 0.1, 0.2 e 0.3 m,
respetivamente.
Finalmente, foi proposto um sistema VLP indoor baseado em redes neurais
convolucionais (CNN). O sistema foi demonstrado experimentalmente usando
luminárias LED como transmissores e uma camara com obturador rotativo
como recetor. O algoritmo de detecção usou um detector de disparo único
(SSD) baseado numa CNN pré configurada (ou seja, MobileNet ou ResNet)
para classificação. O sistema foi validado usando uma configuração de teste
de tamanho real contendo oito luminárias LED. Os resultados obtidos
mostraram que o erro de posicionamento quadrático médio alcançado é de
4.67 e 5.27 cm com os modelos SSD MobileNet e SSD ResNet,
respetivamente. Os resultados da validação mostram que o sistema pode
processar 67 imagens por segundo, permitindo o posicionamento em tempo
real.Programa Doutoral em Engenharia Eletrotécnic
Indoor localization utilizing existing infrastructure in smart homes : a thesis by publications presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Computer and Electronics Engineering, Massey University, Albany, New Zealand
Listed in 2019 Dean's List of Exceptional ThesesIndoor positioning system (IPS) have received significant interest from the research
community over the past decade. However, this has not eventuated into widespread adoption
of IPS and few commercial solutions exist. Integration into Smart Homes could allow for
secondary services including location-based services, targeted user experiences and intrusion
detection, to be enabled using the existing underlying infrastructure. Since New Zealand has
an aging population, we must ensure that the elderly are well looked after. An IPS solution
could detect whether a person has been immobile for an extended period and alert medical
personnel. A major shortcoming of existing IPS is their reliance on end-users to undertake a
significant infrastructure investment to facilitate the localization tasks. An IPS that does
not require extensive installation and calibration procedures, could potentially see
significant uptake from end users. In order to expedite the widespread adoption of IPS
technology, this thesis focuses on four major areas of improvement, namely: infrastructure
reuse, reduced node density, algorithm improvement and reduced end user calibration
requirements. The work presented demonstrates the feasibility of utilizing existing wireless
and lighting infrastructure for positioning and implements novel spring-relaxation and
potential fields-based localization approaches that allow for robust target tracking, with
minimal calibration requirements. The developed novel localization algorithms are
benchmarked against the existing state of the art and show superior performance
Spatial Identification Methods and Systems for RFID Tags
DisertaÄŤnĂ práce je zaměřena na metody a systĂ©my pro měřenĂ vzdálenosti a lokalizaci RFID tagĹŻ pracujĂcĂch v pásmu UHF. Ăšvod je vÄ›nován popisu souÄŤasnĂ©ho stavu vÄ›deckĂ©ho poznánĂ v oblasti RFID prostorovĂ© identifikace a struÄŤnĂ©mu shrnutĂ problematiky modelovánĂ a návrhu prototypĹŻ tÄ›chto systĂ©mĹŻ. Po specifikaci cĂlĹŻ disertace pokraÄŤuje práce popisem teorie modelovánĂ degenerovanĂ©ho kanálu pro RFID komunikaci. DetailnÄ› jsou rozebrány metody měřenĂ vzdálenosti a odhadu smÄ›ru pĹ™Ăchodu signálu zaloĹľenĂ© na zpracovánĂ fázovĂ© informace. Pro účely lokalizace je navrĹľeno nÄ›kolik scĂ©nářů rozmĂstÄ›nĂ antĂ©n. Modely degenerovanĂ©ho kanálu jsou simulovány v systĂ©mu MATLAB. VĂ˝znamná část tĂ©to práce je vÄ›nována konceptu softwarovÄ› definovanĂ©ho rádia (SDR) a specifikĹŻm jeho adaptace na UHF RFID, která vyuĹľitĂ běžnĂ˝ch SDR systĂ©mĹŻ znaÄŤnÄ› omezujĂ. Diskutována je zejmĂ©na problematika prĹŻniku nosnĂ© vysĂlaÄŤe do pĹ™ijĂmacĂ cesty a poĹľadavky na signál lokálnĂho oscilátoru pouĹľĂvanĂ˝ pro směšovánĂ. Prezentovány jsou tĹ™i vyvinutĂ© prototypy: experimentálnĂ dotazovaÄŤ EXIN-1, měřicĂ systĂ©m zaloĹľenĂ˝ na platformÄ› Ettus USRP a antĂ©nnĂ pĹ™epĂnacĂ matice pro emulaci SIMO systĂ©mu. ZávÄ›reÄŤná část je zaměřena na testovánĂ a zhodnocenĂ popisovanĂ˝ch lokalizaÄŤnĂch technik, zaloĹľenĂ˝ch na měřenĂ komplexnĂ pĹ™enosovĂ© funkce RFID kanálu. Popisuje ĂşzkopásmovĂ©/širokopásmovĂ© měřenĂ vzdálenosti a metody odhadu smÄ›ru signálu. Oba navrĹľenĂ© scĂ©náře rozmĂstÄ›nĂ antĂ©n jsou v závÄ›ru ověřeny lokalizaÄŤnĂm měřenĂm v reálnĂ˝ch podmĂnkách.The doctoral thesis is focused on methods and systems for ranging and localization of RFID tags operating in the UHF band. It begins with a description of the state of the art in the field of RFID positioning with short extension to the area of modeling and prototyping of such systems. After a brief specification of dissertation objectives, the thesis overviews the theory of degenerate channel modeling for RFID communication. Details are given about phase-based ranging and direction of arrival finding methods. Several antenna placement scenarios are proposed for localization purposes. The degenerate channel models are simulated in MATLAB. A significant part of the thesis is devoted to software defined radio (SDR) concept and its adaptation for UHF RFID operation, as it has its specialties which make the usage of standard SDR test equipment very disputable. Transmit carrier leakage into receiver path and requirements on local oscillator signals for mixing are discussed. The development of three experimental prototypes is also presented there: experimental interrogator EXIN-1, measurement system based on Ettus USRP platform, and antenna switching matrix for an emulation of SIMO system. The final part is focused on testing and evaluation of described positioning techniques based on complex backscatter channel transfer function measurement. Both narrowband/wideband ranging and direction of arrival methods are validated. Finally, both proposed antenna placement scenarios are evaluated with real-world measurements.
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