Localization of passive UHF RFID Labels with Kalman Filter

Localization via Radio Frequency Identification (RFID) is frequently used in different applications nowadays. It has the advantage that next to its ostensible purpose of identifying objects via their unique IDs it can simultaneously be used for the localization of these objects. In this work it is shown how Received Signal Strength Indicator (RSSI) measurements at different antennae of a passive UHF RFID label can be combined for localization. The localization is only done based on the RSSI measurements and a Kalman Filter (KF). Because of non-linearities in the measurement function it is necessary to incorporate an Extended Kalman Filter (EKF) or an Unscented Kalman Filter (UKF) where simulations have shown that the UKF performs better than the EKF. Additionally to the selection of the filter there are different possibilities to increase the localization accuracy of the UKF: The advantages of using Reference Tags (RT) or more than one tag per trolley (relative positioning) in combination with an Unscented Kalman Filter are discussed and simulations results show that the localization error can be decreased significantly via these methods. Another possibility to increase the localization accuracy and in addition to achieve a more realistic simulation is the consideration of the angle between reader antenna and tag. Simulation results with the incorporation of different numbers of fixed antennae lead to the conclusion that this is a useful surplus in the localization

An IoT-Aware Smart System Exploiting the Electromagnetic Behavior of UHF-RFID Tags to Improve Worker Safety in Outdoor Environments

Recently, different solutions leveraging Internet of Things (IoT) technologies have been adopted to avoid accidents in agricultural working environments. As an example, heavy vehicles, e.g., tractors or excavators, have been upgraded with remote controls. Nonetheless, the community continues to encourage discussions on safety issues. In this framework, a localization system installed on remote-controlled farm machines (RCFM) can help in preventing fatal accidents and reduce collision risks. This paper presents an innovative system that exploits passive UHF-RFID technology supported by commercial BLE Beacons for monitoring and preventing accidents that may occur when ground-workers in RCFM collaborate in outdoor agricultural working areas. To this aim, a modular architecture is proposed to locate workers, obstacles and machines and guarantees the security of RCFM movements by using specific notifications for ground-workers prompt interventions. Its main characteristics are presented with its main positioning features based on passive UHF-RFID technology. An experimental campaign discusses its performance and determines the best configuration of the UHF-RFID tags installed on workers and obstacles. Finally, system validation demonstrates the reliability of the main components and the usefulness of the proposed architecture for worker safety

Recent Advances in Indoor Localization Systems and Technologies

Despite the enormous technical progress seen in the past few years, the maturity of indoor localization technologies has not yet reached the level of GNSS solutions. The 23 selected papers in this book present the recent advances and new developments in indoor localization systems and technologies, propose novel or improved methods with increased performance, provide insight into various aspects of quality control, and also introduce some unorthodox positioning methods

Location-Enabled IoT (LE-IoT): A Survey of Positioning Techniques, Error Sources, and Mitigation

The Internet of Things (IoT) has started to empower the future of many industrial and mass-market applications. Localization techniques are becoming key to add location context to IoT data without human perception and intervention. Meanwhile, the newly-emerged Low-Power Wide-Area Network (LPWAN) technologies have advantages such as long-range, low power consumption, low cost, massive connections, and the capability for communication in both indoor and outdoor areas. These features make LPWAN signals strong candidates for mass-market localization applications. However, there are various error sources that have limited localization performance by using such IoT signals. This paper reviews the IoT localization system through the following sequence: IoT localization system review -- localization data sources -- localization algorithms -- localization error sources and mitigation -- localization performance evaluation. Compared to the related surveys, this paper has a more comprehensive and state-of-the-art review on IoT localization methods, an original review on IoT localization error sources and mitigation, an original review on IoT localization performance evaluation, and a more comprehensive review of IoT localization applications, opportunities, and challenges. Thus, this survey provides comprehensive guidance for peers who are interested in enabling localization ability in the existing IoT systems, using IoT systems for localization, or integrating IoT signals with the existing localization sensors

Minimal Infrastructure Radio Frequency Home Localisation Systems

The ability to track the location of a subject in their home allows the provision of a number of location based services, such as remote activity monitoring, context sensitive prompts and detection of safety critical situations such as falls. Such pervasive monitoring functionality offers the potential for elders to live at home for longer periods of their lives with minimal human supervision. The focus of this thesis is on the investigation and development of a home roomlevel localisation technique which can be readily deployed in a realistic home environment with minimal hardware requirements. A conveniently deployed Bluetooth ® localisation platform is designed and experimentally validated throughout the thesis. The platform adopts the convenience of a mobile phone and the processing power of a remote location calculation computer. The use of Bluetooth ® also ensures the extensibility of the platform to other home health supervision scenarios such as wireless body sensor monitoring. Central contributions of this work include the comparison of probabilistic and nonprobabilistic classifiers for location prediction accuracy and the extension of probabilistic classifiers to a Hidden Markov Model Bayesian filtering framework. New location prediction performance metrics are developed and signicant performance improvements are demonstrated with the novel extension of Hidden Markov Models to higher-order Markov movement models. With the simple probabilistic classifiers, location is correctly predicted 80% of the time. This increases to 86% with the application of the Hidden Markov Models and 88% when high-order Hidden Markov Models are employed. Further novelty is exhibited in the derivation of a real-time Hidden Markov Model Viterbi decoding algorithm which presents all the advantages of the original algorithm, while producing location estimates in real-time. Significant contributions are also made to the field of human gait-recognition by applying Bayesian filtering to the task of motion detection from accelerometers which are already present in many mobile phones. Bayesian filtering is demonstrated to enable a 35% improvement in motion recognition rate and even enables a floor recognition rate of 68% using only accelerometers. The unique application of time-varying Hidden Markov Models demonstrates the effect of integrating these freely available motion predictions on long-term location predictions

Neighborhood Localization Method for Locating Construction Resources Based on RFID and BIM

Construction sites are changing every day, which brings some difficulties for different contractors to do their tasks properly. One of the key points for all entities who work on the same site is the location of resources including materials, tools, and equipment. Therefore, the lack of an integrated localization system leads to increase the time wasted on searching for resources. In this research, a localization method which does not need infrastructure is proposed to overcome this problem. Radio Frequency Identification (RFID) as a localization technology is integrated with Building Information Modeling (BIM) as a method of creating, sharing, exchanging and managing the building information throughout the lifecycle among all stakeholders. In the first stage, a requirements’ gathering and conceptual design are performed to add new entities, data types, and properties to the BIM, and relationships between RFID tags and building assets are identified. Secondly, it is proposed to distribute fixed tags with known positions as reference tags for the RFID localization approach. Then, a clustering method chooses the appropriate reference tags to provide them to an Artificial Neural Network (ANN) for further computations. Additionally, Virtual Reference Tags (VRTs) are added to the system to increase the resolution of localization while limiting the cost of the system deployment. Finally, different case studies and simulations are implemented and tested to explore the technical feasibility of the proposed approach

Indoor Positioning and Navigation

In recent years, rapid development in robotics, mobile, and communication technologies has encouraged many studies in the field of localization and navigation in indoor environments. An accurate localization system that can operate in an indoor environment has considerable practical value, because it can be built into autonomous mobile systems or a personal navigation system on a smartphone for guiding people through airports, shopping malls, museums and other public institutions, etc. Such a system would be particularly useful for blind people. Modern smartphones are equipped with numerous sensors (such as inertial sensors, cameras, and barometers) and communication modules (such as WiFi, Bluetooth, NFC, LTE/5G, and UWB capabilities), which enable the implementation of various localization algorithms, namely, visual localization, inertial navigation system, and radio localization. For the mapping of indoor environments and localization of autonomous mobile sysems, LIDAR sensors are also frequently used in addition to smartphone sensors. Visual localization and inertial navigation systems are sensitive to external disturbances; therefore, sensor fusion approaches can be used for the implementation of robust localization algorithms. These have to be optimized in order to be computationally efficient, which is essential for real-time processing and low energy consumption on a smartphone or robot

Digital Beamforming Techniques for Passive UHF RFID Tag Localization

Radio-frequency identification (RFID) technology is on the way to substitute traditional bar codes in many fields of application. Especially the availability of passive ultra-high frequency (UHF) RFID transponders (or tags) in the frequency band between 860 MHz and 960 MHz has fostered the global application in supply chain management. However, the full potential of these systems will only be exploited if the identification of objects is complemented by accurate and robust localization. Passive UHF RFID tags are cost-effective, very small, extremely lightweight, maintenancefree, rugged and can be produced as adhesive labels that can be attached to almost any object. Worldwide standards and frequency regulations have been established and a wide infrastructure of identification systems is operated today. However, the passive nature of the technology requires a simple communication protocol which results in two major limitations with respect to its use for localization purposes: the small signal bandwidth and the small allocated frequency bandwidth. In the presence of multipath reflections, these limitations reduce the achievable localization accuracy and reliability. Thus, new methods have to be found to realize passive UHF RFID localization systems which provide sufficient performance in typical multipath situations. In this thesis, an enhanced transmission channel model for passive UHF RFID localization systems has been proposed which allows an accurate estimation of the channel behaviour to multipath. It has been used to design a novel simulation environment and to identify three solutions to minimize multipath interference: a) by varying the channel interface parameters, b) by applying diversity techniques, c) by installation of UHF absorbers. Based on the enhanced channel model, a new method for tag readability prediction with high reliability has been introduced. Furthermore, a novel way to rate the magnitude of multipath interference has been proposed. A digital receiver beamforming localization method has been presented which uses the Root MUSIC algorithm for angulation of a target tag and multipath reducing techniques for an optimum localization performance. A new multiangulation algorithm has been proposed to enable the application of diversity techniques. A novel transmitter beamforming localization approach has been presented which exploits the precisely defined response threshold of passive tags in order to achieve high robustness against multipath. The basic technique has been improved significantly with respect to angular accuracy and processing times. Novel experimental testbeds for receiver and transmitter beamforming have been designed, built and used for verification of the localization performance in real-world measurements. All the improvements achieved contribute to an enhancement of the accuracy and especially the robustness of passive UHF RFID localization systems in multipath environments which is the main focus of this researc

Ortsbezogene Anwendungen und Dienste: 9. Fachgespräch der GI/ITG-Fachgruppe Kommunikation und Verteilte Systeme ; 13. & 14. September 2012

Der Aufenthaltsort eines mobilen Benutzers stellt eine wichtige Information für Anwendungen aus den Bereichen Mobile Computing, Wearable Computing oder Ubiquitous Computing dar. Ist ein mobiles Endgerät in der Lage, die aktuelle Position des Benutzers zu bestimmen, kann diese Information von der Anwendung berücksichtigt werden -- man spricht dabei allgemein von ortsbezogenen Anwendungen. Eng verknüpft mit dem Begriff der ortsbezogenen Anwendung ist der Begriff des ortsbezogenen Dienstes. Hierbei handelt es sich beispielsweise um einen Dienst, der Informationen über den aktuellen Standort übermittelt. Mittlerweile werden solche Dienste kommerziell eingesetzt und erlauben etwa, dass ein Reisender ein Hotel, eine Tankstelle oder eine Apotheke in der näheren Umgebung findet. Man erwartet, nicht zuletzt durch die Einführung von LTE, ein großes Potenzial ortsbezogener Anwendungen für die Zukunft. Das jährlich stattfindende Fachgespräch "Ortsbezogene Anwendungen und Dienste" der GI/ITG-Fachgruppe Kommunikation und Verteilte Systeme hat sich zum Ziel gesetzt, aktuelle Entwicklungen dieses Fachgebiets in einem breiten Teilnehmerkreis aus Industrie und Wissenschaft zu diskutieren. Der vorliegende Konferenzband fasst die Ergebnisse des neunten Fachgesprächs zusammen.The location of a mobile user poses an important information for applications in the scope of Mobile Computung, Wearable Computing and Ubiquitous Computing. If a mobile device is able to determine the current location of its user, this information may be taken into account by an application. Such applications are called a location-based applications. Closely related to location-based applications are location-based services, which for example provides the user informations about his current location. Meanwhile such services are deployed commercially and enable travelers for example to find a hotel, a petrol station or a pharmacy in his vicinity. It is expected, not least because of the introduction of LTE, a great potential of locations-based applications in the future. The annual technical meeting "Location-based Applications and Services" of the GI/ITG specialized group "Communication and Dsitributed Systems" targets to discuss current evolutions in a broad group of participants assembling of industrial representatives and scientists. The present proceedings summarizes the result of the 9th annual meeting

A Survey of 3D Indoor Localization Systems and Technologies

Indoor localization has recently and significantly attracted the interest of the research community mainly due to the fact that Global Navigation Satellite Systems (GNSSs) typically fail in indoor environments. In the last couple of decades, there have been several works reported in the literature that attempt to tackle the indoor localization problem. However, most of this work is focused solely on two-dimensional (2D) localization, while very few papers consider three dimensions (3D). There is also a noticeable lack of survey papers focusing on 3D indoor localization; hence, in this paper, we aim to carry out a survey and provide a detailed critical review of the current state of the art concerning 3D indoor localization including geometric approaches such as angle of arrival (AoA), time of arrival (ToA), time difference of arrival (TDoA), fingerprinting approaches based on Received Signal Strength (RSS), Channel State Information (CSI), Magnetic Field (MF) and Fine Time Measurement (FTM), as well as fusion-based and hybrid-positioning techniques. We provide a variety of technologies, with a focus on wireless technologies that may be utilized for 3D indoor localization such as WiFi, Bluetooth, UWB, mmWave, visible light and sound-based technologies. We critically analyze the advantages and disadvantages of each approach/technology in 3D localization