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Using RFID and INS for Indoor Positioning

  • Qing Fu
  • Günther Retscher
Chapter
Part of the Lecture Notes in Geoinformation and Cartography book series (LNGC)

Abstract

This paper describes the current research work in the project UCPNAVI (Ubiquitous Cartograpy for Pedestrian Navigation) and outlines the methods by using active RFID (Radio Frequency Identifi cation) in combination with INS (Inertial Navigation Systems) for positioning. In RFID positioning totally three different methods have been employed, i.e., cell-based positioning, trilateration using ranges to the surrounding RFID transponders (so-called tags) deduced from received signal strength measurements and RFID location fingerprinting. These technologies can be employed depending on the density of the RFID tags in the surrounding environment providing different levels of positioning accuracies. The positioning is restricted, however, to areas where at least one RFID signal can be detected. In order to overcome the lack of coverage of signals of the RFID tags we propose to integrate a low-cost INS in addition. INS measurements would be utilized to calculate the trajectory based on the method of strapdown mechanization. At the same time Kalman Filter would be used to correct the positions and velocity obtained. Since the INS components produce small measurement errors that accumulate over time and cause drift errors, the positions determined by RFID would be needed regularly to eliminate these errors. After a description of the principles and methods for positioning using active RFID the determination of pedestrian trajectories using INS and RFID is described briefly. The approach is verified by field tests and first test results are presented.

Keywords

indoor positioning active RFID INS Kalman Filter sensor fusion 

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References

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Qing Fu
    • 1
  • Günther Retscher
    • 1
  1. 1.Institute of Geodesy and GeophysicsVienna University of TechnologyAustria

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