Range sensor data fusion and position estimation for the iLoc indoor localisation system

  • Authors:
  • S. Knauth;C. Jost;A. Klapproth

  • Affiliations:
  • Stuttgart University of Applied Sciences, HFT Stuttgart, Faculty for Geomatics, Computer Science and Mathematics, Stuttgart, Germany;Lucerne University of Applied Sciences, iHomeLab, the Swiss think tank and lab for intelligent living and building automation, Horw, Switzerland;Lucerne University of Applied Sciences, iHomeLab, the Swiss think tank and lab for intelligent living and building automation, Horw, Switzerland

  • Venue:
  • ETFA'09 Proceedings of the 14th IEEE international conference on Emerging technologies & factory automation
  • Year:
  • 2009

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Abstract

An ultrasound indoor localisation system typically comprises an infrastructure formed by a plurality of fixed nodes, so called beacons. By ultrasound time of flight measurements, the range between a mobile node and some of the fixed beacons at known positions is detected. Given a minimum of 3 such range measurements, the postion of the mobile node can be determined by trilateration. To achieve good accuracy and coverage, even under difficult or disturbed conditions, it is common practice to include more than 3 measurements to calculate a position estimation. The calculation result will somehow average over the reported values. Inclusion of inacurrate measurements will degrade the result. We present an algorithm for selection of the three "most believed" range measurements out of the obtained ranges. The algorithm is employed in the iLoc indoor localisation sytsem.