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Sensors 2018, 18(1), 266;

Smartphone-Based Cooperative Indoor Localization with RFID Technology

Centre for Automation and Robotics (CAR), Spanish Council for Scientific Research (CSIC-UPM), Ctra. de Campo Real km 0,200, Arganda del Rey, Madrid 28500, Spain
Author to whom correspondence should be addressed.
Received: 15 November 2017 / Revised: 9 January 2018 / Accepted: 15 January 2018 / Published: 18 January 2018
(This article belongs to the Special Issue Smartphone-based Pedestrian Localization and Navigation)
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In GPS-denied indoor environments, localization and tracking of people can be achieved with a mobile device such as a smartphone by processing the received signal strength (RSS) of RF signals emitted from known location beacons (anchor nodes), combined with Pedestrian Dead Reckoning (PDR) estimates of the user motion. An enhacement of this localization technique is feasible if the users themselves carry additional RF emitters (mobile nodes), and the cooperative position estimates of a group of persons incorporate the RSS measurements exchanged between users. We propose a centralized cooperative particle filter (PF) formulation over the joint state of all users that permits to process RSS measurements from both anchor and mobile emitters, as well as PDR motion estimates and map information (if available) to increase the overall positioning accuracy, particularly in regions with low density of anchor nodes. Smartphones are used as a convenient mobile platform for sensor measurements acquisition, low-level processing, and data transmission to a central unit, where cooperative localization processing takes place. The cooperative method is experimentally demonstrated with four users moving in an area of 1600 m 2 , with 7 anchor nodes comprised of active RFID (radio frequency identification) tags, and additional mobile tags carried by each user. Due to the limited coverage provided by the anchor beacons, RSS-based individual localization is inaccurate (6.1 m median error), but this improves to 4.9 m median error with the cooperative PF. Further gains are produced if the PDR information is added to the filter: median error of 3.1 m (individual) and 2.6 m (cooperative); and if map information is also considered, the results are 1.8 m (individual) and 1.6 m (cooperative). Thus, for each version of the particle filter, cooperative localization outperforms individual localization in terms of positioning accuracy. View Full-Text
Keywords: smartphone-based indoor positioning; cooperative localization; Bayesian estimation; particle filters; RFID technology smartphone-based indoor positioning; cooperative localization; Bayesian estimation; particle filters; RFID technology

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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Seco, F.; Jiménez, A.R. Smartphone-Based Cooperative Indoor Localization with RFID Technology. Sensors 2018, 18, 266.

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