SALMA: UWB-based Single-Anchor Localization System Using Multipath Assistance

Authors:
Bernhard Großwindhager Graz University of Technology, Austria
Michael Rath Graz University of Technology, Austria
Josef Kulmer Graz University of Technology, Austria
Mustafa Bakr Graz University of Technology, Austria
Carlo Alberto Boano Graz University of Technology, Austria
Klaus Witrisal Graz University of Technology, Austria
Kay Römer Graz University of Technology, Austria

Introduction:

In this paper, the authors present SALMA, a novel low-cost UWB-based indoor localization system that makes use of only one anchor and that does neither require prior calibration nor training. We further study the performance of SALMA in the presence of obstructed line-of-sight conditions, moving objects and furniture, as well as in highly dynamic environments with several people moving around, showing that the system can sustain decimeter-level accuracy with a worst-case average error below 34 cm.An experimental evaluation in an ofice environment with clear line-ofsight has shown that 90% of the position estimates obtained using SALMA exhibit less than 20 cm error, with a median below 8 cm.

Abstract:

Setting up indoor localization systems is often excessively timeconsuming and labor-intensive, because of the high amount of anchors to be carefully deployed or the burdensome collection of ifngerprints. In this paper, we present SALMA, a novel low-cost UWB-based indoor localization system that makes use of only one anchor and that does neither require prior calibration nor training. By using only a crude floor plan and by exploiting multipath reflections, SALMA can accurately determine the position of a mobile tag using a single anchor, hence minimizing the infrastructure costs, as well as the setup time. We implement SALMA on of-the-shelf UWB devices based on the Decawave DW1000 transceiver and show that, by making use of multiple directional antennas, SALMA can also resolve ambiguities due to overlapping multipath components. An experimental evaluation in an ofice environment with clear line-ofsight has shown that 90% of the position estimates obtained using SALMA exhibit less than 20 cm error, with a median below 8 cm. We further study the performance of SALMA in the presence of obstructed line-of-sight conditions, moving objects and furniture, as well as in highly dynamic environments with several people moving around, showing that the system can sustain decimeter-level accuracy with a worst-case average error below 34 cm.

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