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Self-Weighted Multilateration for Indoor Positioning Systems.

Alberto Fornaser1, Luca Maule2, Alessandro Luchetti3

  • 1Department of Industrial Engineering, University of Trento, Via Sommarive 9, 38123 Trento, Italy. alberto.fornaser@unitn.it.

Sensors (Basel, Switzerland)
|February 23, 2019
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This study introduces a new multilateration method for precise tag positioning using beacon distance measurements. The improved technique significantly reduces localization errors compared to commercial systems.

Keywords:
indoor localizationmeasurementmultilaterationultra-wide-banduncertainty

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Area of Science:

  • Robotics
  • Sensor Fusion
  • Navigation Systems

Background:

  • Accurate positioning of movable tags is crucial for various applications.
  • Existing multilateration techniques can be limited by measurement repeatability and calibration.
  • Ultra-Wide-Band (UWB) and ultrasound are common physical principles for distance measurement.

Purpose of the Study:

  • To develop an improved multilateration method for enhanced tag localization accuracy.
  • To introduce a self-supported calibration technique for weighing beacon contributions.
  • To compare the proposed method's performance against a commercial UWB system.

Main Methods:

  • The proposed method utilizes multilateration with weighted beacon contributions.
  • A recurring, self-supported calibration assesses measurement repeatability at different ranges.
  • Two algorithm versions are developed: one-dimensional (isotropic) and 3D.

Main Results:

  • The isotropic solution reduced maximum localization error by approximately 25% (0.60 m).
  • The 3D version further improved accuracy, achieving a maximum error of 0.45 m.
  • The method demonstrated superior measurement quality compared to a commercial UWB system.

Conclusions:

  • The novel multilateration approach significantly enhances tag localization accuracy.
  • Self-supported calibration of measurement repeatability is key to the method's success.
  • The 3D version offers state-of-the-art performance in tag positioning.