Dissertations / Theses on the topic 'Indoor Positioning System'

Three-dimensional visualization refers to the process by which graphical content is created using the Three-dimensional software. While working with Threedimensional visualization, different indoor positioning techniques can be used to detect and track the movement of objects. Combining these two technologies provide the ability to monitor a room and its objects in real time. Positioning is the process of recording the movement of objects or people. Positioning techniques can be used in many different areas such as emergent situations and tracking objects with potential risks as an aid. It is not self-evident how well this kind of a system would work in the given contexts. To address this, the method has consisted of a literature study focused on existing theories of positioning and different factors that affect the positioning outcome and a case study on positioning systems in a number of existing indoor positioning systems. The purpose of this project is to present and evaluate a prototype where an indoor positioning system will be combined with a specific platform which works with simple types of hardware signals to generate three-dimensional models. The goal is to present a system that will have the ability to be used without any infrastructure or external hardware. Different indoor positioning systems will be analyzed as well as their use in various scenarios. This thesis evaluates various technical choices, and provides an overview of some of the existing wireless indoor positioning solutions and the theory and methods used, before describing the case study, including the development process, problems faced, the result, and the experimental testing results. In conclusion, the thesis presents a prototype which is validated to fulfill the basic expectation of a three-dimensional visualized indoor positioning system.
Tredimensionell visualisering refererar till processen genom vilken grafisk innehåll skapas med hjälp av tredimensionell programvara. Under arbetet med tredimensionell visualisering kan olika inomhus positioneringstekniker användas för att upptäcka och spåra rörelser av object. Kombinationen av dessa två tekniker ger möjlighet att övervaka ett rum och dess föremål i realtid. Positionering är processen att spela in rörelser av objekt eller personer. Positionering kan användas i många olika områden såsom nödsituationer och spårning av föremål eller brandmän i enbyggnad som brinner eller detektering av polishundar som är utbildade för att hitta sprängämnen i en byggnad. Det är inte självklart hur bra ett sådant system skulle fungera i de givna sammanhangen. För att ta itu med detta, har metoden bestått av en litteraturstudie inriktat på befintliga teorier om positionering, olika faktorer som påverkar positionerings resultatet samt en fallstudie om positioneringssystem i ett antal befintliga inomhus positioneringssystem. Syftet med detta projekt är att presentera och utvärdera en prototyp där ett inomhuspositioneringssystem kombineras med en specifik plattform som arbetar med enkla typer av hårdvaru signaler för att generera tredimensionella modeller. Målet är att presentera ett system som kommer kunna användas utan någon infrastruktur eller extern hårdvara. Olika inomhus positioneringssystem kommer att analyserar såväl som deras användning i olika scenarier. Denna avhandling utvärderar olika tekniska val och ger en översikt över några av de befintliga trådlösa inomhuspositioneringlösningarna och ger teorin och metoderna, innan fallstudien beskrivs, inklusive: utvecklingsprocessen, problem, resultat och experimentella testresultat. Sammanfattningsvis presenterar avhandlingen en prototyp som valideras för att uppfylla de grundläggande förväntningarna för ett tredimensionellt visualiserat inomhus positioneringssystem.

The purpose of this thesis is to investigate the possibility and feasibility of a platform-independent positioning system capable of determining the location of mobile devices without imposing additional requirements on the hardware and software of the device other than supporting Wi-Fi. Focus is on designing a scalable system capable of positioning devices on multiple sites. The suggested solution uses commercially available Wi-Fi access points to observe the received signal strength when a device probes for nearby access points. The information gathered by the access points is forwarded to a server cluster that uses the signal strength data to determine the location of the device.

A technique is proposed to improve the accuracy of indoor positioning systems based on WIFI radio-frequency signals by using dynamic access points and fingerprints (DAFs). Moreover, an indoor position system that relies solely in DAFs is proposed. The walking pattern of indoor users is classified as dynamic or static for indoor positioning purposes. I demonstrate that the performance of a conventional indoor positioning system that uses static fingerprints can be enhanced by considering dynamic fingerprints and access points. The accuracy of the system is evaluated using four positioning algorithms and two random access point selection strategies. The system facilitates the location of people where there is no wireless local area network (WLAN) infrastructure deployed or where the WLAN infrastructure has been drastically affected, for example by natural disasters. The system can be used for search and rescue operations and for expanding the coverage of an indoor positioning system.

The principal objectives of this research are: to investigate the performance of different fingerprint-based WiFi Indoor Positioning Systems (IPS), analyse historical long-term data signals, detection of signal change points and outliers; then present an enhanced method that generates temporal based fingerprints. The proposed method consists of analysing signal strength profiles over time and detecting points at which the profile behaviour changes. This methodology can be used to dynamically adjust the fingerprint based on environmental factors, and with this select the relevant Wireless Access Points (WAPs) to be used for fingerprinting. The use of an Exponentially Weighted Moving Average (EWMA) Control Chart is investigated for this purpose. A long-term analysis of the WiFi scenery is presented and used as a test-bed for evaluation of state-of-the-art fingerprinting techniques. Data was collected and analysed over a period of 18 months, with over 840 different WAPs detected in over 77,000 observations covering 47 different locations of varying characteristics. A fully functional IPS has been developed and the design and implementation is described in this thesis. The system allows the scanning and recording of WiFi signals in order to define the generation of temporal fingerprints that can create radio-maps, which then allow indoor positioning to occur. This thesis presents the theory behind the concept and develops the technology to create a testable implementation. Experiments and their evaluation are also included. Based on the timestamp experiments the proposed system shows there is still room level accuracy, with a reduction in radio-map size.

This thesis presents a prototype beacon-based indoor positioning system using IR-based triangulation together with various inertial sensors mounted onto the receiver. By applying a Kalman filter, the mobile receivers can estimate their position by fusing the data received from the two independent measurement systems. Furthermore, the system is aimed to operate and conduct all calculations using microcontrollers. Multiple IR beacons and an AGV were constructed to determine the systems performance. Empirical and practical experiments show that the proposed localisation system is capable centimeter accuracy. However, because of hardware limitation the system has lacking update frequency and range. With the limitations in mind, it can be established that the final sensor-fused solution shows great promise but requires an extended component assessment and more advanced localisation estimations method such as an Extended Kalman Filter or particle filter to increase reliability.

Thesis (MTech (Information Technology))--Cape Peninsula University of Technology, 2015.
Recently, the deployment and availability of wireless technology have led to the development of location and positioning services. These Location Based Services (LBSs) are attracting the attention of researchers and mobile service providers. With the importance of ubiquitous computing, the main challenge seen in the LBS is in the mobile positioning or localization within reasonable and certain accuracy. The Global Positioning System (GPS), as a widely known and used navigation system, is only appropriate for use in outdoor environments, due to the lack of line-of-sight (LOS) in satellite signals that they cannot be used accurately inside buildings and premises. Apart from GPS, Wi-Fi is among others, a widely used technology as it is an already existing infrastructure in most places. This work proposes and presents an indoor positioning system. As opposed to an Ad-hoc Positioning System (APS), it uses a Wireless Mesh Network (WMN). The system makes use of an already existing Wi-Fi infrastructure. Moreover, the approach tests the positioning of a node with its neighbours in a mesh network using multi-hopping functionality. The positioning measurements used were the ICMP echo requests, RSSI and RTS/CTS requests and responses. The positioning method used was the trilateral technique, in combination with the idea of the fingerprinting method. Through research and experimentation, this study developed a system which shows potential as a positioning system with an error of about 2 m – 3 m. The hybridization of the methods proves an enhancement in the system though improvements are still required

Under det senaste decenniet har inomhuspositionering fått en ökad popularitet och stått i fokus för forskning och utveckling, eftersom det ger praktiska möjligheter till att spåra och navigera objekt och människor i inomhusmiljöer. Det finns ingen global lösning för inomhuspositionering baserat på en enstaka teknologi såsom det gör för utomhuspositionering med sin satellitbaserade globala positioneringssystem. Många inomhusteknologier står inför många utmaningar såsom låg positioneringsnoggrannhet samt dyr och stor hårdvara. Den här uppsatsen beskriver hur en simpel och kostnadseffektiv lösning, som addresserar problemen med noggrannheten och hårdvarukostnaden, genom en iterativ forskningsmetod, utvecklades. Vår lösning är ett ultraljudsbaserat passivt sändare-mottagare system som kombinerar multilateration som positioneringsteknik och tidsskillnad av ankomst (TDOA) som mätprincip för att beräkna en 3D-position inuti en 4x2x2 m testyta med en övergripande noggrannhet på 16 cm inom ett 95% konfidensintervall. Vi registrerade noggranna TDOA-värden med en komparatorkrets som fungerade som en amplitud-trigger. Det här tillvägagångssättet var mycket enklare än vad andra relaterade arbeten använde sig av, vilket var sampling för att bearbeta inkommande signaler från sändarna.
During the past decade, indoor positioning has gained more popularity and has become a focus of research and development as it provides practical possibilities to track and navigate objects and people in indoor environments. There is no overall solution for indoor positioning based on a single technology like the solution for outdoor positioning with its satellite-based global positioning system. Many indoor positioning technologies today face many challenges such as low positioning accuracy, expensive and large hardware. This thesis describes how a simple and cost-effective solution, that addresses the problem of accuracy and space cost with regards to hardware being used, was developed through an iterative research methodology. Our solution is an ultrasound-based passive receiver-transmitter system that combines multilateration as a positioning technique and time difference of arrival (TDOA) as a measuring principle. This combination is used to calculate a 3D position within a 4x2x2 m test area with an overall accuracy of 16 cm within a 95% confidence interval. We registered accurate TDOA values with a comparator circuit that acts as an amplitude trigger. This approach was much more simple than that of other related works which used sampling to process incoming signals from the transmitters.

Positioning technologies are starting to play an important role in commercial,industrial, and civil applications. Emergency caller ID and positioning in industrialenvironments are important use cases. This thesis performs a systemlevel study of Downlink Time Difference of Arrival positioning in a factorysetting using a ray-tracing radio propagation simulator. Its aims are to investigatethe radio environment in an indoor industrial setting and to evaluate theachievable DL-TDoA based positioning accuracy. The results indicate thatdiffracted links are the most common Non-line-of-sight link type used for positioning.Their mean excess multipath length in respect to direct paths is verylow and makes them a good choice for positioning. Genie line-of-sight detectionand the use of only line-of-sight links for positioning give very largegains in positioning accuracy showing great potential for line-of-sight detectionbased positioning methods. However, simple line-of-sight detection basedon whether the first peak in the CIR is also the strongest peak did not giveany significant performance gains. Our simulations have shown that positioningestimation with built in robustness against outlier measurements leads tobetter performance. Robust estimators performed much better in simulationswith added distance estimation errors. Overall, DL-TDoA positioning appliedto an indoor factory scenario meets the accuracy requirements of 3GPP Rel-16, which state that 80% of UEs must have a positioning error lower than 3m[1]. However, none of the conducted simulations were able to meet the morestringent Rel-17 requirements of <1m for 90% of UEs [2]. Further study stepshave been proposed to address these requirements.
Positionering börjar bli väldigt viktigt inom kommersiell-, industriell-och civilaplikationer.Nödanrops-id samt positionering inom industriell miljö är tvåviktiga användningsområden. Denna uppsats utför en systemnivåundersökningav DL-TDoA positionering inom industriell miljö med hjälp av strålspårningsradio-signalspridnings-simulator. Uppsatsen siktar på att undersöka radiomiljöinom inomhus-industriell miljö och att utvärdera positioneringsnoggrannhetsom kan nås med DL-TDoA. Resultaten visar att diffrakterade länkar ärde vanligaste NLoS(non line-of-sight, ej fri sikt) länkar som används för positionering.Deras medelöverflödighet flervägs längd är väldigt låg i jämförelsemed direktvägs medelöverflödighet längd. Därför är de ett bra val för positionering.Genie line-of-sight(fri sikt) detektering och användning av bara lineof-sight länkar för positionering ger en väldigt stor förstärkning av positioneringsnoggrannhet.Det bevisar att line-of-sight detektion-baserade metoderhar bra potential. Å andra sidan, en enkel line-of-sight detektion baserat på omförsta CIRs toppen också är starkast visade ingen betydlig prestationsförstärkning.Våra simuleringar visade att positioneringsuppskattning med inbyggdrobusthet mot uteliggare leder till bättre prestanda. Robusta uppskattningarhade bättre prestanda i simuleringar med tillagd avstånds-uppskatningsfel. Ihelhet, DL-TDoA positionering tillämpad på inomhusindustriella omständigheteruppfyller noggranhetskraven för 3GPP Rel-16 där 80% av användarutrustningeninte får ha positioneringsfel som är högre än 3 meter. Dock, inga avutförda simuleringar kunde uppfylla striktare Rel-17 krav där 90% av användarutrustningeninte får ha positioneringsfel som är högre än 1 meter. Uppsatsenföreslår hur kraven kan nås i framtidsundersökning.

Indoor positioning systems can be of a great help when trying to local- ize in an indoor environment. To be able to navigate, there is a need for an indoor map that to some degree represent the reality. This thesis aims to come up with a proof of concept of a system that maps rectan- gular objects onto a two dimensional map in an indoor environment. The maps will be drawn with the help of the position of a hand-held device that marks the corners of the objects. A problem that arises is that the error in the positioning can contribute to objects that have the same size and are aligned in reality can vary in size and be misaligned on the map. Another problem is that with the error in the position- ing, the position might end up within an existing object, which leads to a bad user experience. The problems were solved by developing a system, that given a map with objects mapped from the help of posi- tioning, can adjust the shape and positions of the objects based on the mean-values of multiple identical objects. To avoid positions within objects, a function was written that always checks if the positions is within an existing object and if that is the case, then move the correct the position to the closest position outside of the object. The final re- sult was a proof of concept of a system that can generate maps with mapped objects and users that can traverse the map with a good user experience.
Inomhuspositioneringssystem kan vara till stor hjälp när man vill lo- kalisera sig i en inomhusmiljö. För att kunna navigera sig så krävs det en inomhuskarta som i viss mån representerar verkligheten. Den- na avhandling ämnar att komma fram till en konceptvalidering för ett system som ska mappa upp rektangulära objekt på tvådimensio- nella kartor i en inomhusmiljö. Kartorna ritas upp med hjälp av po- sitionen från en handhållen enhet som markerar hörnen på objekten. Problem som uppstår då är att felet från positionen kan få objekt som är av samma storlek och uppställda på rad i verkligheten, att se oli- ka stora ut och vara placerade lite huller om buller på kartan. Ett an- nat problem är att positionen kan med det här felet i positioneringen, komma att befinna sig i ett existerande objekt, vilket leder till en dålig användarupplevelse. Problemen löstes genom att utveckla ett system, som utifrån en karta med objekt mappade med hjälp av positionering, kan justera objektens form och position baserat på medelvärdena av flertalet likadana objekt. För att undvika positioner innanför objekt så skrevs en funktion som hela tiden kollar om positionen befinner sig i något befintligt objekt och om så skulle vara fallet så korrigeras po- sitionen till närmsta position utanför objektet. Slutresultatet blev en konceptvalidering av ett system som kan generera kartor med mappa- de objekt och användare som kan traversera dessa kartor med en god användarupplevelse.

Indoor Positioning Systems lokaliserar människor och objekt inomhus med hjälp av minst tre kända referenspunkter. System för inomhuspositionering som använder kända referenspunkter kallas anchor-based lokalisering medan de som beräknar deras positioner själva kallas anchor-free lokalisering. Syftet med detta arbete är att utveckla en algoritm som är anpassad efter ett anchor-free lokaliseringssystem. Den ska vara oberoende av nätverksuppkopplingen, hårdvaran och hur avstånden mellan mottagare och sensorer beräknats. Utgångspunkten för algoritmen är enbart avstånd mellan en mottagare och tre sensorer vilket kan beskrivas som arbetets huvudsakliga problem. Algoritmen implementerades i Java med en simulering som återspeglar positioneringen i en perfekt miljö och sedan testas på en Android-applikation. Simuleringen tillåter användaren att rita ut flera mätpunkter som skapar en rutt. Dessa mätpunkter utnyttjas för att dynamiskt lokalisera referenspunkterna och mätpunkterna genom att hitta ett minsta avstånd mellan sensorerna. Dessa avstånd kan beskrivas som sidorna för en referenstriangel som möjliggör att ett koordinatsystem kan spännas upp. Resultatet av den empiriska studien visade en felmarginal mellan 0,3-6 m utan signalstörningar, vilket inte var tillräckligt noggrant. Efter att algoritmen implementerats lades fokus på en korrigering som kan itereras igenom för att uppskatta bättre mätvärden för referenstriangeln. Korrigeringen gav positiva resultat med lägre felmarginal. Arbetet kan vidareutvecklas genom att implementeras i ett verkligt IPS-system och algoritmen kan förbättras genom att skapa utökade funktioner som kan hantera fler än tre beacons.

There is a high demand for Indoor Positioning Systems (IPS) due to the wide application possibilities. The main issue for localization by wireless signals in an indoor environment is the multipath propagation problem. Multipath propagation occurs when signals reflects and refract from an object, changing the signals characteristics. Today there is no IPS that can balance the cost, accuracy, and complexity. In January 2019 Bluetooth released a new standard, Bluetooth Low Energy (BLE) 5.1, which enables the ability to measure the Angle of Arrival (AoA) of an incoming signal. The purpose of this thesis is to mitigate the disturbances caused by multipath propagation by conducting a case study. This was done by designing systems that combine different positioning techniques with sensor fusion and evaluating them based on power efficiency, execution time and precision. Two wireless localization techniques were evaluated, trilateration and triangulation, which are based on Received Signal Strength Indication (RSSI) and AoA respectively, along with an Inertial Measurement Unit (IMU). An Extended Kalman Filter EKF was used to fuse the sensor data. The system with the best overall performance uses the AoA signals and a multipath mitigation technique. The system with AoA and IMU had a similar performance but has an overall higher complexity due to the added IMU component. The RSSI system could not satisfy the requirement of precision.
Det finns en stor efterfrågan på inomhus positionssystem (IPS) tack vare de många möjliga tillämpningarna. Det största problemet för inomhuslokalisering med trådlösa signaler i inomhusmiljö är flervägsutbredningsproblemet. Felvägsutbredning inträffar när signaler reflekterar och bryts på ett objekt, och ändrar dess karaktär. Idag finns det inga IPS som kan balansera kostnaden, noggrannhetoch komplexitet. I januari 2019, släppte Bluetooth en ny standard, Bluetooth Low Energy (BLE) 5.1, som gör det möjligt att mäta ankomstvinkeln (AoA) för en inkommande signal. Syftet med denna avhandling är att minska störningarna orsakade av flervägsutbredning genom att utföra en fallstudie. Detta gjordes genom att designa system som kombinerar olika positioneringstekniker med sensor fusion och utvärdera dessa med avseende på energieffektivitet, exekveringstid och precision. Två trådlösa lokaliseringstekniker utvärderades, trilaterering och triangulering, som är baserade på mottagen signalstyrka indikation RSSI och AoA respektive, tillsammans med en tröghetssensor (IMU). Ett Utökat Kalman-Filter (EKF) användes för att kombinera data. Systemet med den överlag bästa prestandan använder AoA-signaler och en teknik för att dämpa flervägsutredningen. Systemet med AoA och IMU hade liknande prestanda men den totala komplexiteten ökade med att lägga till en IMU komponent. RSSI systemet var inte tillräckligt tillfredsställande med avseende på precisionskraven.

RF fingerprinting can solve the indoor positioning problem with satisfactory accuracy, but the methodology depends on the so-called radio map calibrated in the offline phase via manual site-survey, which is costly, time-consuming and somewhat error-prone. It also assumes the RF fingerprint’s signal-spatial correlations to remain static throughout the online positioning phase, which generally does not hold in practice. This is because indoor environments constantly experience dynamic changes, causing the radio signal strengths to fluctuate over time, which weakens the signal-spatial correlations of the RF fingerprints. State-of-the-arts have proposed adaptive RF fingerprint methodology capable of calibrating the radio map in real-time and on-demand to address these drawbacks. However, existing implementations are highly server-centric, which is less robust, does not scale well, and not privacy-friendly. This thesis aims to address these drawbacks by exploring the feasibility of implementing an adaptive RF fingerprint indoor positioning system in a distributed and client-centric architecture using only commodity Wi-Fi hardware, so it can seamlessly integrate with existing Wi-Fi network and allow it to offer both networking and positioning services. Such approach has not been explored in previous works, which forms the basis of this thesis’ main contribution. The proposed methodology utilizes a network of distributed location beacons as its reference infrastructure; hence the system is more robust since it does not have any single point-of-failure. Each location beacon periodically broadcasts its coordinate to announce its presence in the area, plus coefficients that model its real-time RSS distribution around the transmitting antenna. These coefficients are constantly self-calibrated by the location beacon using empirical RSS measurements obtained from neighbouring location beacons in a collaborative fashion, and fitting the values using path loss with log-normal shadowing model as a function of inter-beacon distances while minimizing the error in a least-squared sense. By self-modelling its RSS distribution in real-time, the location beacon becomes aware of its dynamically fluctuating signal levels caused by physical, environmental and temporal characteristics of the indoor environment. The implementation of this self-modelling feature on commodity Wi-Fi hardware is another original contribution of this thesis. Location discovery is managed locally by the clients, which means the proposed system can support unlimited number of client devices simultaneously while also protect user’s privacy because no information is shared with external parties. It starts by listening for beacon frames broadcasted by nearby location beacons and measuring their RSS values to establish the RF fingerprint of the unknown point. Next, it simulates the reference RF fingerprints of predetermined points inside the target area, effectively calibrating the site’s radio map, by computing the RSS values of all detected location beacons using their respective coordinates and path loss coefficients embedded inside the received beacon frames. Note that the coefficients model the real-time RSS distribution of each location beacon around its transmitting antenna; hence, the radio map is able to adapt itself to the dynamic fluctuations of the radio signal to maintain its signal-spatial correlations. The final step is to search the radio map to find the reference RF fingerprint that most closely resembles the unknown sample, where its coordinate is returned as the location result. One positioning approach would be to first construct a full radio map by computing the RSS of all detected location beacons at all predetermined calibration points, then followed by an exhaustive search over all reference RF fingerprints to find the best match. Generally, RF fingerprint algorithm performs better with higher number of calibration points per unit area since more locations can be classified, while extra RSS components can help to better distinguish between nearby calibration points. However, to calibrate and search many RF fingerprints will incur substantial computing costs, which is unsuitable for power and resource limited client devices. To address this challenge, this thesis introduces a novel algorithm suitable for client-centric positioning as another contribution. Given an unknown RF fingerprint to solve for location, the proposed algorithm first sorts the RSS in descending order. It then iterates over this list, first selecting the location beacon with the strongest RSS because this implies the unknown location is closest to the said location beacon. Next, it computes the beacon’s RSS using its path loss coefficients and coordinate information one calibration point at a time while simultaneously compares the result with the measured value. If they are similar, the algorithm keeps this location for subsequent processing; else it is removed because distant points relative to the unknown location would exhibit vastly different RSS values due to the different site-specific obstructions encountered by the radio signal propagation. The algorithm repeats the process by selecting the next strongest location beacon, but this time it only computes its RSS for those points identified in the previous iteration. After the last iteration completes, the average coordinate of remaining calibration points is returned as the location result. Matlab simulation shows the proposed algorithm only takes about half of the time to produce a location estimate with similar positioning accuracy compared to conventional algorithm that does a full radio map calibration and exhaustive RF fingerprint search. As part of the thesis’ contribution, a prototype of the proposed indoor positioning system is developed using only commodity Wi-Fi hardware and open-source software to evaluate its usability in real-world settings and to demonstrate possible implementation on existing Wi-Fi installations. Experimental results verify the proposed system yields consistent positioning accuracy, even in highly dynamic indoor environments and changing location beacon topologies.

Thesis (M.Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1999.
Includes bibliographical references (leaves 61-62).
I present here the detailed design for a low frequency radio navigation system called the Building Positioning System (BPS). This system is designed to work indoors, where the microwave radio signals of the Global Positioning System (OPS) cannot be received. Potential applications for this system range from asset tracking, security, and human-computer interface, to robot navigation and the management of services as diverse as medical care and postal delivery. I first present the issues surrounding its conceptual design and then describe in detail the component level implementation of the prototype BPS system, which I have designed and built but not yet tested as a whole. I also discuss the test procedures which will accompany the deployment of that prototype system in its initial configuration in its test building, as well as further research that is required to make the system scalable and manufacturable.
by Matthew S. Reynolds.
M.Eng.

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2007.
Includes bibliographical references (p. 91-93).
Precise positioning is crucial to many applications involving autonomous robots in indoor environments. Current solutions to the indoor localization problem are either both highly unreliable and inaccurate (like GPS based systems), or hugely expensive (such as the iGPS system). In this thesis we propose, design and build a low-cost, robust and highly accurate indoor localization system using laser light sources. The system is composed of three transmitting laser modules arranged in a straight line and a receiver module mounted on the mobile robot. The system calculates the coordinates of the mobile robot by using triangulation algorithms which require precisely measured values of the angles of the receiver with respect to the three laser emitters. Results from practical testing of the system in an aircraft wing assembly set-up have been found to be extremely encouraging. Using our system, the mobile robotic arm could be localized accurately within error margins defined approximately by Gaussian distributions centered at the object's true coordinate values and with standard deviations of 0.1778 mm, 0.1016 mm and 0.3352 mm in the x, y and z coordinate directions respectively. The system is also used to detect height drop in the arm due to its weight as it extends to perform fitting operations on the skin of the wing. Feedback from the laser localization system is used to adjust the position of the tip of the robotic arm in order to perform a sequence of high precision docking tasks within the aircraft wing.
by Srujan Linga.
S.M.

In this paper, a new concept for ultrasonic indoor positioning based on instantaneous frequency of ultrasonic signals is presented. Nonlinear phase characteristics of ultrasonic transducers introduce a frequency deviation in ultrasonic signals. By sweeping at very fast rates, a large spike in the deviation is introduced. The artefacts observable in instantaneous frequency estimations are highly localized and present an opportunity for accurate frequency detection. In order to be useful, the artefacts need to take place within the pulse and have sufficient magnitude for accurate processing. The system consists of a transducer transmitter and receiver pair, which have a center frequency of 40kHz and a bandwidth of 460Hz. In order to incorporate more transmitters, a time-division multiple access (TDMA) scheme is applied to ensure orthogonality of signals. The concept includes four ultrasonic transmitters and a single receiver, which can uniquely identify each transmitter by a distinct signal sweep. Linear chirp signals are used to form narrow pulses and ensure no interference in the TDMA scheme. The received signal is amplified and passed through a phase-locked loop (PLL) to detect the chirp signals. Accurate instantaneous frequency detection can be done on the voltage-controlled oscillator (VCO) of the PLL, which has a narrower bandwidth than the overall signal sweep. The instantaneous frequency estimation methods are largely explored in this work and consider two methods: the Hilbert transform and a zero-crossings method. This work highlights some of the advantages and disadvantages of both methods. Time of flight (ToF) in this system can ultimately be obtained by considering the instantaneous frequency estimations and the time for one particular frequency to be transmitted and received.

The use of smartphones for positioning and navigation is mostly limited to outdoor settings. Indoors, where GPS signals are too inaccurate for positioning, an alternative must be used. This project aimed at producing an indoor positioning system which could be both configured and used by an end user organization without equipping its buildings with proprietary hardware. The prerequisites were that a complete digital representation of the building floors is available, and that the floors have a sufficient amount of WiFi access points. Our system measures radio signal strength from existing WiFi infrastructure using a smartphone. This data is sent to a backend and is used to position a device using two different methods: trilateration and fingerprinting. The finished system can position a user with an accuracy of approximately four meters using fingerprinting instead of trilateration as it yielded the best results. The building used for testing was scanned using a smartphone equipped with our application, something that we would expect an end user to be able to do.
Användandet av smartphones för positionering och navigering är mestadels inriktat på utomhusanvändning. Inomhus är GPS signaler inte tillräckligt noggranna för positionering, och ett alternativ måste användas. Det här projektets mål var att producera ett inomhuspositioneringssystem som kan konfigureras och användas av slutanvändarorganisationen utan att behöva utrusta sina byggnader med proprietär hårdvara. Förutsättningarna är att en komplett digital representation av byggnaden finns tillgänglig, och att våningsplanen har tillräckligt många WiFi basstationer. Vårt system mäter radiosignalstyrka från den existerande WiFi infrastrukturen. Denna data skickas till en backend och används i två olika metoder: trilateration och fingerprinting. Det slutgiltiga systemet kan positionera en användare med en träffsäkerhet på ungefär fyra meter när fingerprintingmetoden används då den producerade det bästa resultatet. Byggnaden som systemet testades i skannades av en smartphone med vår applikation, en sak som vi förväntar oss att en slutanvändare skulle kunna göra själv.

The main purpose of this thesis work is to find and compare different network characteristics of MPS (Mobile Positioning System) in the different wireless technology domains. Since decades ago MNO’s (Mobile Network Operators) added many new services based on the geographical areas of subscribers and their needs. Here we define wireless networks and go through different types of technologies and do the comparison when they collect different types of data for their location-based services and see if we could have the same accuracy with 2G (second generation) of mobile network as like as 3G (third generation) and higher. Finally, we will come up with a proposal for new age technology.

This thesis aims to investigate a triangulation system for indoor positioning in two dimensions (2D). The system was implemented using three Pixy2 vision sensors placed on a straight baseline. A Pixy2 consists of a camera lens and an image sensor (Aptina MT9M114) as well as a microcontroller (NXP LPC4330), and other components. It can track one or multiple colours, or a combination of colours.  To position an object using triangulation, one needs to determine the angles (α) to the object from a pair of known observing points (i.e., any pair of the three Pixy2s' placed in fixed positions on the baseline in this project). This is done from the Pixy2s' images. Using the Pinhole Camera Model, the tangent of the angle, tan(α), is found to have a linear relation with the displacement Δx in the image plane (in pixels), namely, tan(α) = k Δx, where k is a constant depending on the specific Pixy2. A wooden test board was made specially to determine k for all the Pixy2s. It had distance marks made in two dimensions and had a Pixy2 affixed at the origin. By placing a coloured object at three different sets of spatial sampling points (marks), the constant k for each Pixy2 was determined with the error variance of < 5%. Position estimations of the triangulation system were conducted using all three pairs formed from the three Pixy2s and placing the positioned object at different positions in the 2D plane on the board. A combination using estimation values from all three pairs to make a more accurate estimate was also evaluated. The estimation results show the positioning accuracy ranging from 0.03678 cm to 2.064 cm for the z-coordinate, and from 0.02133 cm to 0.9785 cm for the x-coordinate, which are very satisfactory results.      The vision sensors were quite sensitive to the light environment when finely tuned to track one object, which therefore has a significant effect on the performance of the vision sensor-based triangulation.      An extension of the system to use more than three Pixy2s has been looked into and shown to be feasible. A method for auto-calibrating the Pixy2s' positions on the baseline was suggested and implemented. After auto-calibration, the system still performed satisfactory position estimations.

International Telemetering Conference Proceedings / October 22-25, 2001 / Riviera Hotel and Convention Center, Las Vegas, Nevada
This project investigates the feasibility of position detection in an office or industrial setting. The objective is to design a low-cost positioning system that uses the unlicensed 5.7 GHz ISM band, with centimeter accuracy and limited range. During the conceptual design phase of the system, indoor channel models will be investigated to determine which of a variety of architectures will be useful. For triangulating the position, an array of widely spaced stationary receivers and a mobile transmitter is proposed.

Localization is one of the most interesting research areas in wireless networks. It is mostly used for tracking and monitoring applications such as traffic monitoring, search and rescue, navigation and so on. A good quality system can be defined from its accuracy when operating in severe interference environments that contaminate the signals and therefore reduce the system performance. The main issue for localization is channel propagation, e.g., line of sight or non-line of sight channel which should be studied in order to improve the system efficiency.    In order to perform a localization, most algorithms use two steps: ranging and positioning. For ranging, the two popular techniques that are widely used for distance measurement are received signal strength (RSS) and time of arrival (TOA). RSS ranging technique uses the power of the received signals to identify the distance between a transmitter and a receiver. TOA ranging technique uses time of the signal traveling between a transmitter and a receiver to identify the distance, thus it requires synchronization. The measurements are processed by using a localization algorithm afterwards. However, these techniques suffer from multipath fading and other errors, so there always exists error in the estimated position.    In this thesis, TOA ranging technique is used for different estimation methods. Simulation results are performed using MATLAB, while the real results are obtained from Pozyx indoor positioning platform. Several estimation algorithms comprising of maximum likelihood (ML), linearized least square (LLS), weighted centroid (WC), and fingerprinting (FP) are studied in detail. The testing area is indoor environment which is suitable for LOS, NLOS and combined situations. The measured data is then used for ranging and localization. We concentrate on comparing and discussing these results in this thesis.

Dissertação de mestrado integrado em Engenharia Electrónica Industrial e Computadores (área de especialização em Informática Industrial)
In this thesis, the indoor positioning problem is approached using an Android platform. This approach is based in tests with a set of algorithms and techniques. The performance of each algorithm and technique, in an indoor environment, is measured using data from a dataset of a known location mapped with a smartphone in a static and dynamic context, enabling the possibility to perform a wide range of tests and get useful insights. This thesis approach uses a developed dataset to test the performance of a set of algorithms in different contexts using the Android platform. The dataset has information relative to Wi-Fi signal strength, acceleration and magnetic field strength in different locations inside the room. Algorithms were tested using the useful information provided by the dataset. After those tests, it was concluded that fingerprinting is more suitable than multilateration indoors since multilateration can become unstable due its need of a distance estimation. The algorithm that returned better results was the Minimum Mean Square Error (MMSE) algorithm. Using this algorithm, a functional Android indoor positioning application was built.
Nesta dissertação é abordado o problema de posicionamento em interiores usando a plataforma Android. Esta abordagem é baseada em testes de um grupo de algoritmos e técnicas. Em interiores, a performance de cada algoritmo e técnica é medida usando dados provenientes de um dataset. Este dataset diz respeito a uma área conhecida mapeada com um smartphone em contexto estático e dinâmico, de forma a abrir a possibilidade de efetuar uma diferente variedade de testes e obter várias estatisticas de interesse. Nesta dissertação, é desenvolvido um dataset que é usado como base para testar o performance de um grupo de algoritmos em diferentes contextos, usando para tal a plataforma Android. Este dataset tem informação relativa à intensidade do sinal Wi-Fi, aceleração e campos magnéticos em diferentes posições da sala. Os algoritmos foram testados usando o dataset desenvolvido. Depois dos testes efetuados, concluíu-se que o fingerprinting é mais adequado que a multilateração para efeitos de posicionamento indoor, isto porque a multilateração pode ficar instável devido á sua dependência de uma estimativa da distância. O algoritmo com melhores resultados foi o MMSE. Usando este algoritmo, uma aplicação Android para posicionamento em interiores foi desenvolvida.

碩士
義守大學
機械與自動化工程學系碩士班
93
With the prevalence and development of the Internet, the network infrastructure begins to extend from the original wired network to the wireless network. In recent years, the development of wireless network attracts much attention in various applications. Due to the widespread use of the wireless network. One of the applications is personal or device locating service of location. With the increasing demand of the positioning service, people pay much attention to the indoor wireless positioning system based on Wireless Local Area Networks (WLAN). Nowadays, GPS is the most extensively used for locating service in outdoor environment but GPS deployment is not cost-effective. This research describes the development and implementation of an indoor wireless positioning systems based on IEEE 802.11x wireless network. We developed programs to obtain the values of signal strength transmitted from various Access Points (AP) in the wireless network. As the distance between transmitter and receiver changes, the received signal strength changes accordingly. This research aims to use the variations of signal strength combined with the probabilistic model of indoor wireless channels to calculate the position of the mobile terminal and to design a digital filter to improve positioning accuracy.

碩士
國立中正大學
電機工程所
95
This thesis describes a positioning system based on IEEE802.15.4/ZigBee, which can obtain user’s position at an indoor environment. In IEEE 802.15.4, the Received Signal Strength Indicator (RSSI) is used to determine the quality of the communication between nodes. We use the RSSI value to build the signal database. There is a model to map the RSSI to real position by a Neural Network. When a user wants to know where he is. The only thing needs to do is to put the RSSI value to the system, and obtain the position. We propose an error correction algorithm to reduce the error distance because the accuracy is not good enough. The error distance of the result will become high when the user is moving such that we implement a Kalman filter to correct the error in movement.

碩士
國立中正大學
光機電整合工程所
96
The purpose of this thesis is in order to achieve an embedded system. The system solve the question of differentiating location in indoor environment. The system gets strength messages of electromagnetic wave by equipment of RFID. Equipment of RFID communicate strength messages to platform. Algorithm is processing data and send the result to screen that display it on platform. The system applies to localization in a size in indoor or outdoor. There are two setting of location with four tags or eight tags. And there are three different algorithms to deal with localization. We can observe fit and unfit quality of algorithms and number of tags for locates fine in the experimentation. The purpose that use equipment of RFID and embedded system is in order to reduce the cost. This also can make user more convenient. Under the conditions of cost down and convenient this system also enhances the fine of localization as far as possible. I wish that the paper can present some useful information for localization correlation researcher.

碩士
國立臺灣海洋大學
電機工程學系
94
In recent years，techniques and applications of indoor positioning system have received much attention. Radio Frequency Identification (RFID) technology has been widely used in indoor environment, due to the rapid development of semiconductor manufacturing, digital signal processing and microwave device techniques. At present, RFID-based positioning systems for indoor environment, need at least two receivers to estimate the position of signal source, thus become a problem with regard to cost nature of RFID system. Another concern in indoor positioning technology is how to accurately extract line-of-sight (LOS) component and estimate its direction of arrival (AOA) and time of arrival (TOA). When applied to the indoor environment, RFID system will incur co-channel interference (CCI), multipath and no LOS effects, therefore, facing great challenge to accurate positioning. In the thesis, we propose a TOA-AOA indoor positioning algorithm suitable for indoor environment, using a single receiver to estimate TOA and AOA of the signal source. In this method, the joint model of multi-user and multipath radio propagation channel is used, wherein one user is desired and others are treated as CCI sources. The method uses a matched filter bank to suppress CCI, the T-MUSIC algorithm to estimate TOA of the desired user, a temporal filter to extract LOS component, and the S-MUSIC algorithm to estimate the AOA of desired user. Computer simulation results show that the proposed method is very effective for target positioning in indoor environment.

碩士
國立交通大學
資訊科學與工程研究所
102
A great variety of indoor positioning systems for mobile devices have different advantages and limitations. In this work, we propose an integrated indoor positioning system to integrate Wi-Fi positioning, Pedestrian Tracking System (PTS) and Photo positioning with one Kalman filter. By using our single intuitive positioning UI, the median positioning error of PTS+Wi-Fi positioning and Photo positioning are as low as 2.82m and 0.74m respectively. The Photo positioning can provide a high accuracy positioning service by investigating the geometric relations between the images of points of interest (POI) in the photo and their location in the real world based on the principle of photo imaging. A Photo positioning algorithm based on the geometric similarity in photo imaging is presented in this work, and an integrated indoor positioning system is developed for Android smartphone platforms.

博士
國立臺灣科技大學
電機工程系
103
Internet of Things (IoT) is an emerging topic of research recently. In the future, all things in the real world will connect to the virtual world. It will be useful if we can locate an object in the real world as well as identify it in the virtual world. However, it is not easy to accurately position a target in the indoor environment. For one thing, the radio waves propagate in an indoor environment is affected by multipath interference. It makes serious estimation errors when the target is positioned. For another, when each target has a transceiver the overall power consumption of the whole system is considerable. In this work, a passive RFID system is proposed to solve the two important technological problems. Because the passive RFID has the advantages of low power consumption and low cost, it has become a preferred wireless technology for indoor positioning system in recent years. we first design a dual-channel 15-bit UHF passive CMOS RFID tag prototype that can work at sensitivity lower than --20 dBm. Measurement result shows that the sensitivity of the proposed passive tag chip can reach down to --21.2 dBm. Such result corresponds to a 19.6-m reader-to-tag distance under 36-dBm EIRP and 0.4-dBi tag antenna. It provides the long-range tag for our system. Having the long-range dual-band tag, we propose a novel indoor positioning system. The proposed indoor positioning system employs a probabilistic algorithm to reduce the positioning error. The cumulative probability for positioning error within is 87.5\%. The power consumption of the RF part of the proposed system is 24.63 dBm, which is the lowest compared with the prior art. Furthermore, the proposed system can be easily expanded a larger system.

碩士
國立雲林科技大學
電子工程系
105
Global Positioning System (GPS) has been developed for many years and is widely used in various fields. It provides users with instant access to location information via smart devices. But GPS in the indoor environment is vulnerable to the shadow of complex buildings and multi-path effects, resulting in loss of GPS positioning function. Most people live in the indoor environment for more than 80% of the time, so the demand for indoor positioning system, has become an important issue. In this thesis, Visible Light Communication (VLC) technology combined with ARM Microcontrollers and Smartphone devices is integrated to serve as lighting, com-munication and positioning. To make the positioning system easy to be implemented in the Smartphone, the Audio Jack port is used to connect smartphone with VLC receiver. We use the Received Signal Strength Indicator (RSSI) to determine the distance be-tween the reference point and the target point in the indoor environment. And the loca-tion of the target point is estimated by the trilateral measurement and location method of the intelligent mobile phone, and finally the indoor positioning result is presented in the intelligent mobile phone. We use time division multiplexing (TDM) technology in the VLC system for timing management, to avoid interference from adjacent lights. Finally, the indoor location measurement results in the prototype positioning system show the maximum position error of 3cm and the average position error of 1.86cm. It can be concluded that the VLC-based Smartphone indoor positioning system can accurately estimate the location of the user in the indoor environment by using the Smartphone.

碩士
國立中央大學
通訊工程學系
103
As development of wireless networks advance, a variety of positioning technologies have been proposed. The positioning technology using existing infrastructure for positioning has become the most attractive research topic. The current positioning technologies have many disadvantages, such as complicated estimation, calculation and offline measurements. In order to solve the above problems, this thesis proposes the simple indoor positioning system, which uses the existing wireless network and estimates the location according to the variance of the sets of discovered access points. Our experimental results confirmed that the simple estimation method is able to measure the locations of users.

碩士
國立臺灣科技大學
電機工程系
103
Applications and services for smart handheld devices have garnered considerable attention worldwide, as have applications for Indoor Location-based Services (Indoor LBS). Improving their indoor positioning accuracy is a significant challenge. In recent years, many indoor positioning studies have used radio frequency for positioning; however, a signal’s susceptibility to environmental interference can decrease positioning accuracy. Increasing positioning accuracy is a complex problem and remains to be solved. Indoor positioning systems typically use only a signal transmitter (Wi-Fi AP) and receiver to acquire reference point data. The systems then use the K-Nearest Neighbor algorithm (KNN) or a Multilateration algorithm for positioning. Consequently, positioning accuracy is limited by both the positioning algorithm and the use of a single source for acquisition of reference point data. This study utilizes the novel Integrated Heterogeneous Networks Indoor Positioning System (IHNIPS) with low-energy Bluetooth Beacon to obtain positioning data. A fingerprint algorithm is then applied to revise the multilateration algorithm and define the fuzzy area to improve the accuracy of subspace selection. Last, novel threshold mechanisms are used to choose the transmitter for positioning and thereby improve current positioning accuracy. Experimental results show that the average error distance is 1.29m for Wi-Fi AP and 1.33m for Beacon. And the average error distance is 1.21m in the proposed Integrated Heterogeneous Networks Indoor Positioning System. The IHNIPS outperforms both Wi-Fi AP and Beacon. Thus, positioning accuracy is improved.

Tese de Doutoramento - Programa Doutoral em Engenharia Electrónica e Computadores
Positioning technologies are ubiquitous nowadays. From the implementation of the global positioning system (GPS) until now, its evolution, acceptance and spread has been unanimous, due to the underlying advantages the system brings. Currently, these systems are present in many different scenarios, from the home to the movie theatre, at work, during a walk in the park. Many applications provide useful information, based on the current position of the user, in order to provide results of interest. Positioning systems can be implemented in a wide range of contexts: in hospitals to locate equipment and guide patients to the necessary resources, or in public spaces like museums, to guide tourists during visits. They can also be used in a gymnasium to point the user to his next workout machine and, simultaneously, gather information regarding his fitness plan. In a congress or conference, the positioning system can be used to provide information to its participants about the on-going presentations. Devices can also be monitored to prevent thefts. Privacy and security issues are also important in positioning systems. A user might not want to be localized or its location to be known, permanently or during a time interval, in different locations. This information is therefore sensitive to the user and influences directly the acceptance of the system itself. Concerning outdoor systems, GPS is in fact the system of reference. However, this system cannot be used in indoor environment, due to the high attenuation of the satellite signals from non-line-of-sight conditions. Another issue related to GPS is the power consumption. The integration of these devices with wireless sensor networks becomes prohibitive, due to the low power consumption profile associated with devices in this type of networks. As such, this work proposes an indoor positioning system for wireless sensor networks, having in consideration the low energy consumption and low computational capacity profile. The proposed indoor positioning system is composed of two modules: the received signal strength positioning module and the stride and heading positioning module. For the first module, an experimental performance comparison between several received signal strength based algorithms was conducted in order to assess its performance in a predefined indoor environment. Modifications to the algorithm with higher performance were implemented and evaluated, by introducing a model of the effect of the human body in the received signal strength. In the case of the second module, a stride and heading system was proposed, which comprises two subsystems: the stride detection and stride length estimation system to detect strides and infer the travelled distance, and an attitude and heading reference system to provide the full three-dimensional orientation stride-by-stride. The stride detection enabled the identification of the gait cycle and detected strides with an error percentage between 0% and 0.9%. For the stride length estimation two methods were proposed, a simplified method, and an improved method with higher computational requirements than the former. The simplified method estimated the total distance with an error between 6.7% and 7.7% of total travelled distance. The improved method achieved an error between 1.2% and 3.7%. Both the stride detection and the improved stride length estimation methods were compared to other methods in the literature with favourable results. For the second subsystem, this work proposed a quaternion-based complementary filter. A generic formulation allows a simple parameterization of the filter, according to the amount of external influences (accelerations and magnetic interferences) that are expected, depending on the location that the device is to be attached on the human body. The generic formulation enables the inclusion/exclusion of components, thus allowing design choices according to the needs of applications in wireless sensor networks. The proposed method was compared to two other existing solutions in terms of robustness to interferences and execution time, also presenting a favourable outcome.
Os sistemas de posicionamento fazem parte do quotidiano. Desde a implementação do sistema GPS (Global Positioning System) até aos dias que correm, a evolução, aceitação e disseminação destes sistemas foi unânime, derivada das vantagens subjacentes da sua utilização. Hoje em dia, eles estão presentes nos mais variados cenários, desde o lar até́ à sala de cinema, no trabalho, num passeio ao ar livre. São várias as aplicações que nos fornecem informação útil, usando como base a descrição da posição atual, de modo a produzir resultados de maior interesse para os utilizadores. Os sistemas de posicionamento podem ser implementados nos mais variados contextos, como por exemplo: nos hospitais, para localizar equipamento e guiar os pacientes aos recursos necessários, ou nas grandes superfícies públicas, como por exemplo museus, para guiar os turistas durante as visitas. Podem ser igualmente utilizados num ginásio para indicar ao utilizador qual a máquina para onde se deve dirigir durante o seu treino e, simultaneamente, obter informação acerca desta mesma máquina. Num congresso ou conferência, o sistema de localização pode ser utilizado para fornecer informação aos seus participantes sobre as apresentações que estão a decorrer no momento. Os dispositivos também podem ser monitorizados para prevenir roubos. Existem também questões de privacidade e segurança associados aos sistemas de posicionamento. Um utilizador poderá não desejar ser localizado ou que a sua localização seja conhecida, permanentemente ou num determinado intervalo de tempo, num ou em vários locais. Esta informação é por isso sensível ao utilizador e influencia diretamente a aceitação do próprio sistema. No que diz respeito aos sistemas utilizados no exterior, o GPS (ou posicionamento por satélite) é de facto o sistema mais utilizado. No entanto, em ambiente interior este sistema não pode ser usado, por causa da grande atenuação dos sinais provenientes dos satélites devido à falta de linha de vista. Um outro problema associado ao recetor GPS está relacionado com as suas características elétricas, nomeadamente os consumos energéticos. A integração destes dispositivos nas redes de sensores sem fios torna-se proibitiva, devido ao perfil de baixo consumo associado a estas redes. Este trabalho propõe um sistema de posicionamento para redes de sensores sem fio em ambiente interior, tendo em conta o perfil de baixo consumo de potência e baixa capacidade de processamento. O sistema proposto é constituído por dois módulos: o modulo de posicionamento por potência de sinal recebido e o módulo de navegação inercial pedestre. Para o primeiro módulo foi feita uma comparação experimental entre vários algoritmos que utilizam a potência do sinal recebido, de modo a avaliar a sua utilização num ambiente interior pré-definido. Ao algoritmo com melhor prestação foram implementadas e testadas modificações, utilizando um modelo do efeito do corpo na potência do sinal recebido. Para o segundo módulo foi proposto um sistema de navegação inercial pedestre. Este sistema é composto por dois subsistemas: o subsistema de deteção de passos e estimação de distância percorrida; e o subsistema de orientação que fornece a direção do movimento do utilizador, passo a passo. O sistema de deteção de passos proposto permite a identificação das fases da marcha, detetando passos com um erro entre 0% e 0.9%. Para o sistema de estimação da distância foram propostos dois métodos: um método simplificado de baixa complexidade e um método melhorado, mas com maiores requisitos computacionais quando comparado com o primeiro. O método simplificado estima a distância total com erros entre 6.7% e 7.7% da distância percorrida. O método melhorado por sua vez alcança erros entre 1.2% e 3.7%. Ambos os sistemas foram comparados com outros sistemas da literatura apresentando resultados favoráveis. Para o sistema de orientação, este trabalho propõe um filtro complementar baseado em quaterniões. É utilizada uma formulação genérica que permite uma parametrização simples do filtro, de acordo com as influências externas (acelerações e interferências magnéticas) que são expectáveis, dependendo da localização onde se pretende colocar o dispositivo no corpo humano. O algoritmo desenvolvido permite a inclusão/exclusão de componentes, permitindo por isso liberdade de escolha para melhor satisfazer as necessidades das aplicações em redes de sensores sem fios. O método proposto foi comparado com outras soluções em termos de robustez a interferências e tempo de execução, apresentando também resultados positivos.

This research work presents of study of ultra-wide band (UWB) indoor positioning considering different type of obstacles that can affect the localization accuracy. In the actual warehouse, a variety of obstacles including metal, board, worker and other obstacles will have NLOS (non-line-of-sight) impact on the positioning of the logistics package, which influence the measurement of the distance between the logistics package and the anchor , thereby affecting positioning accuracy. A new developed method attempts to improve the accuracy of UWB indoor positioning, through and improved positioning algorithm and filtering algorithm. In this project, simulate the warehouse environment in the laboratory, several simulation proves that the used Kalman filter algorithm and Markov algorithm can effectively reduce the error of NLOS. Experimental validation is carried out considering a mobile tag mounted on a robot platform.
Este trabalho de pesquisa apresenta um estudo de posicionamento de banda ultra-larga (UWB) em ambientes internos considerando diferentes tipos de obstáculos que podem afetar a precisão de localização. No armazém real, uma variedade de obstáculos incluindo metal, placa, trabalhador e outros obstáculos terão impacto NLOS (não linha de visão) no posicionamento do pacote logístico, o que influencia a medição da distância entre o pacote logístico e a âncora, afetando assim a precisão do posicionamento. Um novo método desenvolvido tenta melhorar a precisão do posicionamento interno UWB, através de um algoritmo de posicionamento e algoritmo de filtragem aprimorados. Neste projeto, para simular o ambiente de warehouse em laboratório, diversas simulações comprovam que o algoritmo de filtro de Kalman e o algoritmo de Markov usados podem efetivamente reduzir o erro de NLOS. A validação experimental é realizada considerando um tag móvel montado em uma plataforma de robô.

In robotics, the decision capabilities according to the surrounding environment evaluation are under constant evolution, subject to sudden changes, with the aim of merging the behavior of robots and humans based on sensorial data. Even though it is a complicated task, every year new solutions are built and the complexity of this task has been by-passed enabling better results that contribute to more realistic solutions. The main difficulties in the solutions developed in this area are related to the independent movement control in indoor spaces once that is necessary the use of precise positioning systems necessary for the correct localization input data to the robots ensuring the best action order as quickly as possible. The research and development process presented in this thesis is related to the need of finding an appropriate solution for the indoor positioning systems applied to an autonomous drone. However, due to the construction materials of this type of buildings, it is not possible to use systems based on global position systems (GPS). Therefore, with the conclusion of the trainee program associated with this thesis, the output is a control system for autonomous drones based on the indoor position, capable of making warehouse inventories using Radio Frequency Identification (RFID) technology. During the development process of a modular system, several solutions were considered in response to the issues and objectives of each module organized taking into account its significance for the final product. In the last project phase, it was developed a control module to support the integration of each part and also allowing the inclusion of necessary future modules.
Na área da robótica, a capacidade de decisão em prol da avaliação do ambiente envolvente é uma capacidade em constante evolução e sujeita a alterações repentinas, com o objectivo de aproximar o comportamentos dos robôs ao comportamento humano com base em dados sensoriais. Embora esta tarefa seja de elevada complexidade, o desenvolvimento da tecnologia utilizada para tal, tornou possível alcançar cada vez melhores resultados o que contribui para o desenvolvimento de soluções cada vez mais próximas da realidade. As principais dificuldades sentidas aquando do desenvolvimento de soluções nesta área consistem à mobilidade autônoma em ambientes fechados uma vez que é necessário assegurar a precisão dos sistema de localização utilizados, de forma a possibilitar que robô tenha informação necessária acerca da sua localização relativa e assim agir em concordância com o objectivo e no menor tempo possível. O processo de investigação e desenvolvimento associado a esta dissertação recai sobre a necessidade de encontrar soluções para a localização em interiores de forma a possibilitar voo autónomo de drones capaz de efectuar o controlo de stock em armazéns que possibilitem o voo do mesmo, uma vez que as características dos ambientes internos impossibilitam o uso do sistemas baseados na posição global ou qualquer outro tipo de localização geográfica devido aos materiais que compõem a sua estrutura. Assim sendo, do estágio associado a esta dissertação, resultou um sistema de controlo para drones autônomos capazes de efetuar inventário, com recurso à tecnologia de identificação por rádio frequência, baseado no posicionamento interno. Dado ser um processo faseado, diversas soluções foram estudadas em resposta aos problemas e objetivos característicos de cada um dos diferentes módulos, organizados prioritariamente de acordo com sua relevância para o resultado final. Numa última fase do projecto, será desenvolvida uma solução capaz de interligar todos os módulos desenvolvidos para que desta forma seja possível apresentar uma solução que sustente o desenvolvimento futuro de módulos necessário.
Mestrado em Engenharia de Computadores e Telemática

碩士
國立清華大學
電機工程學系
104
Recently, the drone-related applications are more and more popular such as photography, mapping, real estate and disaster response. In this thesis, the indoor positioning and tracking system for drones is proposed. It includes three parts: positioning component locates position of specified wireless device; tracking component tracks the selected object by pattern recognition; and movement decision component decides the drone’s movement. We have implemented the modified cell of origin (CoO) indoor positioning algorithm with the wireless device, which is the one limits its communication range and processes some calculation with the built-in microcontroller. For the tracking component, we have implemented tracking-learning-detection (TLD) algorithm. TLD is a computer vision algorithm that tracks unknown objects and recognizes object patterns. If tracking is successful, the margin of error will be less than 10 cm. The movement decision component computes feedback from positioning and tracking components to generate the drone’s movement. It positions objects to the center of image and directs the drone to the location commanded by the user. Finally, we propose a system which combines the CoO indoor positioning algorithm, the TLD algorithm, and the movement decisions for drones. The system locates the position of drone with the wireless device, tracks objects through drone’s camera, aims drone’s camera to the object, and flies the drone to desired locations. The test results show 2 m accuracy of positioning, and improved successful tracking rate of 33% higher than other tracking algorithms as control groups. The positioning algorithm contributes to the environment model unnecessary and the scalable coverage of positioning. Moreover, the wireless device’s size of 3 cm * 2 cm * 2 cm makes the system portable and the power consumption of 49.9 mW under 3.0 V operation voltage on a 850 mAh battery keeps the wireless device working over 2 days.

碩士
銘傳大學
電腦與通訊工程學系碩士班
105
People spend 80% of their time in indoors, however, the global positioning system cannot be used in indoors. Currently, indoor positioning system has difficulty to give a 100% of positioning because of environmental influences including pedestrian, WiFi etc.. It becomes crucial to increase the positioning accuracy, especially on dynamic environment. In this study, a wireless network system consisted of XBEE sensors, arduino and raspberry pi is constructed as a new positioning system. The XBEE sensors are used to collect the RSSI signal strength from the wireless network. The positioning process is given by the off-line database construction and on-line positioning. Then the RSSI signal strength and a fingerprint method are used to calculate the position. In the off-line stage, the collected RSSI signal is analyzed and established to be extreme value, average value, distance and noise ratio as the database connected to the on-line positioning. Up to 90% of poisoning accuracy is obtained in a 3m x 3m and 4m x 4m static (without interference) environment. By adding obstacles in the static environment, the RSSI noise increases and obviously affect the positioning accuracy in the dynamic environment. By adding one more sensor in the center of a dynamic environment and updating the off-line database by using the noise parameter, the 90% positioning accuracy in the 3m x 3m dynamic environment is obtained. The 80% positioning accuracy in the 4m x 4m dynamic environment is also obtained in real time.

博士
國立成功大學
建築學系碩博士班
100
With the advancement of personal mobile technology, the application of combining augmented reality (AR) technique with location based services (LBS) has come true. However, in view of the fact that GPS signal lacks of accuracy and can not reach the interior of the construction, this research focuses on the development of indoor mobile augmented reality position tracking system. Taking high environmental adaptability, and high system maintainability as goals, we devoted to realize precise line of sight tracking technique for indoor AR position tracking service. Based on the practical and theory case analysis, we apply infrared invisible marker recognition techniques and head-first tracking skill to the developed system, Head Marker Tracking Augmented Reality (HMTAR). The system can be extendedly applied indoor or outdoor and has AR image recording, sharing, retrieving, and virtual path guiding abilities, which all are tested through practical assessments with good results. Through this paper, we wish to provide another feasible option for future indoor AR location based services.

碩士
國立中興大學
通訊工程研究所
100
In recent years, the sensor units of the wireless sensor network have made tremendous progress, and it has been used in a wide variety of applications. Indoor positioning system is the important one of those applications. The most well-known positioning system is GPS (global positioning system). GPS has been researched and developed for many years, and provides great accuracy in the location system. However, GPS not only requires a LOS (line of sight) to satellite, but it also needs high cost to implement the system. As the result, we cannot implement GPS for indoor positioning system owing to its signal which easily influenced by building in indoor environment and the receivers which cannot keep line of sight to satellite. To build an indoor positioning environment we need inexpensive devices. For these reasons, we use WSN to implement an indoor positioning system. The thesis applies IEEE 802.15.4/ZigBee technology to construct an indoor wireless sensor networks environment. We find the distance between beacon node and unknown node by using RSSI and the pre-collection database. Finally, we use the signal strength of two intersected circles algorithm and indoor map information to calculate the position of unknown node.

碩士
國立臺灣科技大學
電機工程系
102
With the technology evolvement in recent years, the era of mobile communication has gradually changed how people think traditionally. The users of technological products such as smart phones and tablet PCs are emerging such that there are more and more wireless network connections available in public premises allowing people to use their mobile devices to go online. In the past people are used to finding out their current positions or destinations through space plan diagram. However, with the popularization of smart devices, now the current position in indoor space can be located based on the positioning calculation by wireless network devices and smart devices. The most important factor of the indoor space positioning is the environment factor. The issue to be investigated in this study is how to prevent the changes in space pattern from reducing the accuracy of indoor positioning. Several reference points have been installed in the research environment, and the NFC mechanism has been used to readout the data of these reference points. If people in this environment are willing to provide current information of reference points, a learning curve can be calculated for each reference point. The automatic learning of reference point under environmental change will lead to the reliable information of reference point. The sensor has been used for the correction calculation of positioning. If the user’s position has been moved during the interval of every positioning, the information obtained by the sensor can be used for position correction. In this study a learning approach based on reference point has been introduced in order to calculate the reliable reference point data and the sensor correction approach, and development a positioning system learning mechanism through wireless network connection. Due the change in external environment, the traditional statistical approach will require more than 150 times of learning for the reference points, while the method proposed in this study will only require 100 times of learning to achieve the learning objective. This indicates that the reference point learning has been accelerated, and the learning efficiency has been improved. By using three units of AP for positioning in the environment of this research, the average positioning error has been improved from 1.61 m to 1.46 m with the positioning accuracy enhancement of 9.3%, thus improving the user satisfaction and usage rate of positioning system.

碩士
國立臺灣大學
電機工程學研究所
95
This study attempts to design an indoor positioning system by 5 active 433 MHz RFID tags, and a reader in the powered wheelchair, to identify the position of the electric powered wheelchair (EPW) locally. The tags was distributed on the exits of elevator in the 2nd and 3rd floors, the outside of the doors at Labs 341, 343, 345,and 349 in the building (#2) of the Department of Electrical Engineering, National Taiwan University. The results were presented the related amplitude of the RFID signals from the 5 active tags shown a different magnitudes which can be characterized to identify the position of EPW stably. The other method attempts to enlarge the space of detection by the same 5 tags. Through the K-means clustering, the detecting space can be clustered into several adjoining regions. Therefore, this study supports the possibility of the 3-D indoor RFID positioning and navigation.

碩士
國立中央大學
通訊工程學系在職專班
103
In the development of Indoor Positioning System, a wide range of technology is universal available. Any wireless related technology which can achieve positioning can be adapted. With Wi-Fi solution becomes ubiquitous it is a vital technology to support, in our day-to-day life. In fact, we are covered by many Wi-Fi signals wherever we are. Along with it being a built-in feature on modern smartphones, therefore Wi-Fi technology is the most commonly obtainable wireless technology. This thesis proposes to use the Power Level (PL) in Wi-Fi Access Point (AP) to support indoor positioning. The APs periodically sends beacons with unique Service Set Identifier (SSID), which carries the coordinates and corresponding PL value. AP broadcasts beacons using different power levels, one at a time. Smartphone can easily collects the visible APs with certain power levels and then find out the 2 intersections of any pair of nearest APs. Using the coordinates of visible APs, we can filter out the available 4 intersections within viewable range. Using these filtered intersection points, we can find out the center point of the polygon, which is the estimated position of the smartphone. Simulation results reveal the derived error of positioning is tolerable.

The advancements of the indoor positioning system (IPS) in the recent years have been immense, yet we do not see the standardization of any solution. The system which is being used in many public scenarios is the Wi-Fi technology and the solution which we propose in this dissertation would not require change of infrastructure, but rather reusing existing one and simply enhancing it. This solution is low-cost and with relatively high precision considering current precision of Global Positioning System (GPS) of five meters. In this dissertation prototype is designed with motorized directional antennas using signal strength of two ESP8266. These position measurements are calculated and presented via micro controller and a Wi-Fi enabled device – ESP8266. Together with Yagi antenna, this solution has shown extremely good IPS characteristics and possibility to be implemented in real-case scenarios.

碩士
中國文化大學
資訊管理研究所
97
With the increasing development and application on wireless communication, and the demand of positioning with wireless equipment, Location-based Service(LBS) has become an indispensable wireless service today. The primary goal of this study is to evolve an efficient and accurate positioning system via the characteristics of RFID and algorithm. In relevant study on RFID, it is difficult to meet accurate positioning and inexpensive budget simultaneously. This study applies ‘triangle space convergence’ which surrounds an object to be positioned with a triangle in an experimental space and positioning the object by narrowing the triangle. Therefore, approved by the above experiment, accurate positioning can be meet with the our method and decrease the use of equipments.

碩士
國立臺灣大學
資訊工程學研究所
104
Benefit from the wide deployment of Light Emitting Diodes (LED), visible light communication technology has become an active research topic full of commercialization potentials. Taking advantage of this recent development, in this thesis, we proposes LiBeamScanner, an indoor positioning system that utilizes only a single custom light bulb and a light sensor to achieve extremely high positioning accuracy. With only a single light bulb as the transmitter, this system can perform extremely accurate positioning in environments without dense deployment of illuminaries. And the system only utilizes a simple light sensor in the receiver rather than a camera, and has low complexity and low energy consumption. This enables our design to be adopted in systems with more stingent constraints such as wearables. At the transmitting side, we borrow the idea of projectors to send information to corresponding location without interfering neighboring areas by controlling LCD pixels to generate narrow light beams, enabling fine-grained indoor positioning. Moreover, we propose a novel design utilizing dual lenses in the transmitter to modulate the information of stand-off distance, i.e. the height information, in the transmitted signals. Evaluation results of our prototype show that the error is less than 5 cm in most cases and the median error does not exceed 2 cm for the 2-dimensional position estimation, and 17 cm for the 3-dimensional position estimation.