766 research outputs found

    A Survey of Positioning Systems Using Visible LED Lights

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    ยฉ 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

    LocaRDS: A Localization Reference Data Set

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    The use of wireless signals for the purposes of localization enables a host of applications relating to the determination and verification of the positions of network participants ranging from radar to satellite navigation. Consequently, this has been a longstanding interest of theoretical and practical research in mobile networks and many solutions have been proposed in the scientific literature. However, it is hard to assess the performance of these in the real world and, more importantly, to compare their advantages and disadvantages in a controlled scientific manner. With this work, we attempt to improve the current state of art methodology in localization research and to place it on a solid scientific grounding for future investigations. Concretely, we developed LocaRDS, an open reference data set of real-world crowdsourced flight data featuring more than 222 million measurements from over 50 million transmissions recorded by 323 sensors. We demonstrate how we can verify the quality of LocaRDS measurements so that it can be used to test, analyze and directly compare different localization methods. Finally, we provide an example implementation for the aircraft localization problem and a discussion of possible metrics for use with LocaRDS

    LoRa ToA-Based Localization Using Fingerprint Map

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    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ๊ณต๊ณผ๋Œ€ํ•™ ์ปดํ“จํ„ฐ๊ณตํ•™๋ถ€, 2019. 2. ์ „ํ™”์ˆ™.Localization is one of the essential elements in Internet of Things (IoT) applications. Especially, LoRa which is one of the Low-power wide area network (LPWAN) technologies has suitable features for localization such as low power consumption, long range, and low cost of employment. However, the existing LoRa localization methods have limitations in terms of localization possible area and accuracy. In the area where there are less than three gateways, it is impossible to estimate location using the existing algorithms. And the existing LoRa localization algorithms show large estimation error in noisy environment such as urban. In this paper, we propose LoRa ToA-based localization using Fingerprint map to tackle the issues. First, we propose localization algorithm to estimate location even in the area where there are less than three gateways. In addition, to calculate ToA-based distances which are used in the algorithm, we propose a LoRa Time Synchronization Protocol that is suitable for LoRa network. Second, we use fingerprint map to reduce localization error caused by noisy environment. Since we construct fingerprint map utilizing static end-devices, the overhead to use the fingerprint map can be alleviated. The simulation results show that, compared with other schemes, the proposed localization scheme significantly expands localization possible area and improves the localization accuracy.์œ„์น˜ ์ถ”์ •์€ Internet of Things (IoT) ์–ดํ”Œ๋ฆฌ์ผ€์ด์…˜๋“ค์˜ ํ•„์ˆ˜ ๊ธฐ๋Šฅ ๋“ค ์ค‘์— ํ•˜๋‚˜์ด๋‹ค. ํŠนํžˆ, LoRa ๋Š” ์ €์ „๋ ฅ, ์žฅ๊ฑฐ๋ฆฌ, ๊ทธ๋ฆฌ๊ณ  ์ €๋น„์šฉ๊ณผ ๊ฐ™์€ IoT localization ์— ์ ํ•ฉํ•œ ํŠน์ง•๋“ค์„ ๊ฐ€์ง€๊ณ  ์žˆ๋‹ค. ํ•˜์ง€๋งŒ, ๊ธฐ์กด LoRa ์œ„์น˜์ถ”์ • ๋ฐฉ๋ฒ•์—๋Š” ์œ„์น˜ ์ถ”์ • ๊ฐ€๋Šฅ ์ง€์—ญ์ด ์ œํ•œ๋œ๋‹ค๋Š” ์ ๊ณผ ์ •ํ™•๋„๊ฐ€ ๋‚ฎ๋‹ค๋Š” ๋ฌธ์ œ์ ์ด ์žˆ๋‹ค. ๊ฒŒ์ดํŠธ์›จ์ด๊ฐ€ 3๊ฐœ ๋ฏธ๋งŒ์ธ ์ง€์—ญ์—์„œ๋Š” ๊ธฐ์กด Lora ์œ„์น˜ ์ถ”์ • ๋ฐฉ๋ฒ•์œผ๋กœ ์œ„์น˜ ์ถ”์ •์ด ๋ถˆ๊ฐ€๋Šฅํ•˜๋‹ค. ๋˜ํ•œ, ์‹ค์ œ ๋„์‹ฌ๊ณผ ๊ฐ™์ด noise ๊ฐ€ ์‹ฌํ•œ ํ™˜๊ฒฝ์—์„œ๋Š” ์ •ํ™•๋„๊ฐ€ ๋งค์šฐ ๋‚ฎ๋‹ค. ์ด๋Ÿฌํ•œ ๋ฌธ์ œ์ ๋“ค์„ ํ•ด๊ฒฐํ•˜๊ธฐ ์œ„ํ•ด, ๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” Fingerprint map ์„ ์ด์šฉํ•˜๋Š” LoRa ToA ๊ธฐ๋ฐ˜ ์œ„์น˜ ์ถ”์ • ๋ฐฉ๋ฒ•์„ ์ œ์•ˆํ•œ๋‹ค. ์ฒซ ๋ฒˆ์งธ๋กœ, ์šฐ๋ฆฌ๋Š” ๊ฒŒ์ดํŠธ์›จ์ด์˜ ๊ฐœ์ˆ˜์— ์ œํ•œ ์—†์ด ์–ด๋Š ๊ณณ์ด๋“  ์œ„์น˜์ถ”์ •์„ ๊ฐ€๋Šฅํ•˜๊ฒŒ ํ•˜๋Š” ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ์ œ์•ˆํ•œ๋‹ค. ์ถ”๊ฐ€๋กœ, ์•Œ๊ณ ๋ฆฌ์ฆ˜์— ์‚ฌ์šฉ๋  ToA ๊ธฐ๋ฐ˜ ๊ฑฐ๋ฆฌ๋ฅผ ๊ตฌํ•˜๊ธฐ ์œ„ํ•ด, ๊ธฐ์กด ๋ฐฉ์‹์ด ์•„๋‹Œ LoRa ์ ํ•ฉํ•œ LoRa ์‹œ๊ฐ„ ๋™๊ธฐํ™” ํ”„๋กœํ† ์ฝœ์„ ์ œ์•ˆํ•œ๋‹ค. ๋‘ ๋ฒˆ์งธ๋กœ, noise ๊ฐ€ ์‹ฌํ•œ ํ™˜๊ฒฝ์œผ๋กœ ์ธํ•ด ๋ฐœ์ƒํ•˜๋Š” ์˜ค๋ฅ˜๋ฅผ ์ค„์ด๊ธฐ ์œ„ํ•ด fingerprint map ์„ ์ด์šฉํ•œ๋‹ค. ์šฐ๋ฆฌ๋Š” ๊ธฐ์กด ๊ณ ์ •๋˜์–ด ์žˆ๋Š” ๋‹จ๋ง ๊ธฐ๊ธฐ๋“ค์„ ํ™œ์šฉํ•˜๊ธฐ ๋•Œ๋ฌธ์—, fingerprint map ์„ ์‚ฌ์šฉํ•จ์œผ๋กœ์จ ๋ฐœ์ƒํ•˜๋Š” ์˜ค๋ฒ„ํ—ค๋“œ๋ฅผ ์ค„์ผ ์ˆ˜ ์žˆ๋‹ค. ์ œ์•ˆ ๋ฐฉ๋ฒ•์— ๋Œ€ํ•œ ์„ฑ๋Šฅ ์ธก์ • ๊ฒฐ๊ณผ, ์ œ์•ˆํ•˜๋Š” ๋ฐฉ๋ฒ•์€ ๊ธฐ์กด LoRa ์œ„์น˜ ์ถ”์ • ๋ฐฉ๋ฒ•์œผ๋กœ ์ถ”์ •์ด ๋ถˆ๊ฐ€๋Šฅํ•œ ์ง€์—ญ์—์„œ๋„ ์ถ”์ •์„ ๊ฐ€๋Šฅํ•˜๊ฒŒ ํ•จ์œผ๋กœ์จ ์ถ”์ • ๊ฐ€๋Šฅ ๋ฒ”์œ„๋ฅผ ๋„“ํ˜”๊ณ , ์‹ฌํ•œ noise ๋กœ ์ธํ•ด ์ƒ๊ธฐ๋Š” ์˜ค๋ฅ˜๋„ ๋ณด์ •ํ•จ์œผ๋กœ์จ ์ •ํ™•๋„๋ฅผ ํฌ๊ฒŒ ํ–ฅ์ƒ์‹œ์ผฐ๋‹ค.Chapter 1. Introduction 1 Chapter 2. System Model 5 Chapter 3. LoRa Time Synchronization Protocol 6 Chapter 4. Proposed Localization Algorithm 8 Chapter 5. Performance Evaluation 15 Chapter 6. Conclusion 23 Bibliography 24 Abstract in Korean 26Maste

    Exploiting Structural Signal Information in Passive Emitter Localization

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    The operational use of systems for passive geolocation of radio frequency emitters poses various challenges to single sensor systems or sensor networks depending on the measurement methods. Position estimation by means of direction finding systems often requires complex receiver and antenna technique. Time (Difference) of Arrival methods (TDOA, TOA) are based on measurements regarding the signal propagation duration and generally require broadband communication links to transmit raw signal data between spatially separated receivers of a sensor network. Such bandwidth requirements are particularly challenging for applications with moving sensor nodes. This issue is addressed in this thesis and techniques that use signal structure information of the considered signals are presented which allow a drastic reduction of the communication requirements. The advantages of using knowledge of the signal structure for TDOA based emitter localization are shown using two exemplary applications. The first case example deals with the passive surveillance of the civil airspace (Air Traffic Management, ATM) using a stationary sensor network. State of the art airspace surveillance is mainly based on active radar systems (Primary Surveillance Radar, PSR), cooperative secondary radar systems (Secondary Surveillance Radar, SSR) and automatic position reports from the aircraft itself (Automatic Dependent Surveillance-Broadcast, ADS-B). SSR as well as ADS-B relies on aircrafts sending transponder signals at a center frequency of 1090 MHz. The reliability and accuracy of the position reports sent by aircrafts using ADS-B are limited and not sufficient to ensure safe airspace separation for example of two aircrafts landing on parallel runways. In the worst case, the data may even be altered with malicious intent. Using passive emitter localization and tracking based on multilateration (TDOA/hyperbolic localization), a precise situational awareness can be given which is independent of the content of the emitted transponder signals. The high concentration of sending targets and the high number of signals require special signal processing and information fusion techniques to overcome the huge amount of data. It will be shown that a multilateration network that employs those techniques can be used to improve airspace security at reasonable costs. For the second case, a concept is introduced which allows TDOA based emitter localization with only one moving observer platform. Conventional TDOA measurements are obtained using spatially distributed sensor nodes which capture an emitted signal at the same time. From those signals, the time difference of arrival is estimated. Under certain conditions, the exploitation of signal structure information allows to transfer the otherwise only spatial into a spatial and temporal measurement problem. This way, it is possible to obtain TDOA estimates over multiple measurement time steps using a single moving observer and to thus localize the emitter of the signals. The concept of direct position determination is applied to the single sensor signal structure TDOA scheme and techniques for direct single sensor TDOA are introduced. The validity and performance of the presented methods is shown in theoretical analysis in terms of Cramรฉr-Rao Lower Bounds, Monte-Carlo simulations and by evaluation of real data gained during field experiments

    Efficient Time of Arrival Calculation for Acoustic Source Localization Using Wireless Sensor Networks

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    Acoustic source localization is a very useful tool in surveillance and tracking applications. Potential exists for ubiquitous presence of acoustic source localization systems. However, due to several significant challenges they are currently limited in their applications. Wireless Sensor Networks (WSN) offer a feasible solution that can allow for large, ever present acoustic localization systems. Some fundamental challenges remain. This thesis presents some ideas for helping solve the challenging problems faced by networked acoustic localization systems. We make use of a low-power WSN designed specifically for distributed acoustic source localization. Our ideas are based on three important observations. First, sounds emanating from a source will be free of reflections at the beginning of the sound. We make use of this observation by selectively processing only the initial parts of a sound to be localized. Second, the significant features of a sound are more robust to various interference sources. We perform key feature recognition such as the locations of significant zero crossings and local peaks. Third, these features which are compressed descriptors, can also be used for distributed pattern matching. For this we perform basic pattern analysis by comparing sampled signals from various nodes in order to determine better Time Of Arrivals (TOA). Our implementation tests these ideas in a predictable test environment. A complete system for general sounds is left for future wor

    Efficient Time of Arrival Calculation for Acoustic Source Localization Using Wireless Sensor Networks

    Get PDF
    Acoustic source localization is a very useful tool in surveillance and tracking applications. Potential exists for ubiquitous presence of acoustic source localization systems. However, due to several significant challenges they are currently limited in their applications. Wireless Sensor Networks (WSN) offer a feasible solution that can allow for large, ever present acoustic localization systems. Some fundamental challenges remain. This thesis presents some ideas for helping solve the challenging problems faced by networked acoustic localization systems. We make use of a low-power WSN designed specifically for distributed acoustic source localization. Our ideas are based on three important observations. First, sounds emanating from a source will be free of reflections at the beginning of the sound. We make use of this observation by selectively processing only the initial parts of a sound to be localized. Second, the significant features of a sound are more robust to various interference sources. We perform key feature recognition such as the locations of significant zero crossings and local peaks. Third, these features which are compressed descriptors, can also be used for distributed pattern matching. For this we perform basic pattern analysis by comparing sampled signals from various nodes in order to determine better Time Of Arrivals (TOA). Our implementation tests these ideas in a predictable test environment. A complete system for general sounds is left for future wor

    In Pursuit of Aviation Cybersecurity: Experiences and Lessons From a Competitive Approach

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    The passive and independent localization of aircraft has been the subject of much cyberphysical security research. We designed a multistage open competition focusing on the offline batch localization problem using opportunistic data sources. We discuss setup, results, and lessons learned

    Efficient Time of Arrival Calculation for Acoustic Source Localization Using Wireless Sensor Networks

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    Acoustic source localization is a very useful tool in surveillance and tracking applications. Potential exists for ubiquitous presence of acoustic source localization systems. However, due to several significant challenges they are currently limited in their applications. Wireless Sensor Networks (WSN) offer a feasible solution that can allow for large, ever present acoustic localization systems. Some fundamental challenges remain. This thesis presents some ideas for helping solve the challenging problems faced by networked acoustic localization systems. We make use of a low-power WSN designed specifically for distributed acoustic source localization. Our ideas are based on three important observations. First, sounds emanating from a source will be free of reflections at the beginning of the sound. We make use of this observation by selectively processing only the initial parts of a sound to be localized. Second, the significant features of a sound are more robust to various interference sources. We perform key feature recognition such as the locations of significant zero crossings and local peaks. Third, these features which are compressed descriptors, can also be used for distributed pattern matching. For this we perform basic pattern analysis by comparing sampled signals from various nodes in order to determine better Time Of Arrivals (TOA). Our implementation tests these ideas in a predictable test environment. A complete system for general sounds is left for future wor
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