2,257 research outputs found

    RePos : relative position estimation of UHF-RFID tags for item-level localization

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    Radio frequency identification (RFID) technology brings tremendous applications in location-based services. Specifically, ultra-high frequency (UHF) RFID tag positioning based on phase (difference) of arrival (PoA/PDoA) has won great attention, due to its better positioning accuracy than signal strength-based methods. In most cases, such as logistics, retailing, and smart inventory management, the relative orders of the objects are much more attractive than absolute positions with centimetre-level accuracy. In this paper, a relative positioning (RePos) approach based on inter-tag distance and direction estimation is proposed. In the RePos positioning system, the measured phases are reconstructed based on unwrapping method. Then the distances from antenna to the tags are calculated using the distance differences of pairs of antenna's positions via a least-squares method. The relative relationships of the tags, including relative distances and angles, are obtained based on the geometry information extracted from PDoA. The experimental results show that the RePos RFID positioning system can realize about 0.28-meter ranging accuracy, and distinguish the levels and columns without ambiguity

    RF Localization in Indoor Environment

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    In this paper indoor localization system based on the RF power measurements of the Received Signal Strength (RSS) in WLAN environment is presented. Today, the most viable solution for localization is the RSS fingerprinting based approach, where in order to establish a relationship between RSS values and location, different machine learning approaches are used. The advantage of this approach based on WLAN technology is that it does not need new infrastructure (it reuses already and widely deployed equipment), and the RSS measurement is part of the normal operating mode of wireless equipment. We derive the Cramer-Rao Lower Bound (CRLB) of localization accuracy for RSS measurements. In analysis of the bound we give insight in localization performance and deployment issues of a localization system, which could help designing an efficient localization system. To compare different machine learning approaches we developed a localization system based on an artificial neural network, k-nearest neighbors, probabilistic method based on the Gaussian kernel and the histogram method. We tested the developed system in real world WLAN indoor environment, where realistic RSS measurements were collected. Experimental comparison of the results has been investigated and average location estimation error of around 2 meters was obtained

    A phase-based technique for localization of uhf-rfid tags moving on a conveyor belt: Performance analysis and test-case measurements

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    A new phase-based technique for localization and tracking of items moving along a conveyor belt and equipped with ultrahigh frequency-radio frequency identification (UHF-RFID) tags is described and validated here. The technique is based on a synthetic-array approach that takes advantage of the fact that the tagged items move along a conveyor belt whose speed and path are known apriori. In this framework, a joint use is done of synthetic-array radar principles, knowledge-based processing, and efficient exploitation of the reader-tag communication signal. The technique can be easily implemented in any conventional reader based on an in-phase and quadrature receiver and it does not require any modification of the reader antenna configurations usually adopted in UHF-RFID portals. Numerical results are used to investigate the performance analysis of such methods, and also to furnish system design guidelines. Finally, the localization capability is also demonstrated through a measurement campaign in a real conveyor belt scenario, showing that a centimeter-order accuracy in the tag position estimation can be achieved even in a rich multipath environment

    Indoor localization systems-tracking objects and personnel with sensors, wireless networks and RFID

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    Advances in ubiquitous mobile computing and rapid spread of information systems have fostered a growing interest in indoor location-aware or location-based technologies. In this paper we will introduce the primary technologies used in indoor localization systems by classifying them in three categories: Non-RF technologies, Active-RF technologies and Passive-RF technologies. Both commercialized products and research prototypes in all categories are involved in our discussion. The Passive-RF technologies are further divided into “Mobile tag” and “Mobile reader” systems. We expect such classification can cover most of the indoor localization systems. Features of these systems are briefly compared at the end of this paper

    Enabling Communication Technologies for Automated Unmanned Vehicles in Industry 4.0

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    Within the context of Industry 4.0, mobile robot systems such as automated guided vehicles (AGVs) and unmanned aerial vehicles (UAVs) are one of the major areas challenging current communication and localization technologies. Due to stringent requirements on latency and reliability, several of the existing solutions are not capable of meeting the performance required by industrial automation applications. Additionally, the disparity in types and applications of unmanned vehicle (UV) calls for more flexible communication technologies in order to address their specific requirements. In this paper, we propose several use cases for UVs within the context of Industry 4.0 and consider their respective requirements. We also identify wireless technologies that support the deployment of UVs as envisioned in Industry 4.0 scenarios.Comment: 7 pages, 1 figure, 1 tabl
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