A Self-Calibrating Localization Solution for Sport Applications with UWB Technology

Sensors (Basel). 2022 Dec 1;22(23):9363. doi: 10.3390/s22239363.

Abstract

This study addressed the problem of localization in an ultrawide-band (UWB) network, where the positions of both the access points and the tags needed to be estimated. We considered a fully wireless UWB localization system, comprising both software and hardware, featuring easy plug-and-play usability for the consumer, primarily targeting sport and leisure applications. Anchor self-localization was addressed by two-way ranging, also embedding a Gauss-Newton algorithm for the estimation and compensation of antenna delays, and a modified isolation forest algorithm working with low-dimensional set of measurements for outlier identification and removal. This approach avoids time-consuming calibration procedures, and it enables accurate tag localization by the multilateration of time difference of arrival measurements. For the assessment of performance and the comparison of different algorithms, we considered an experimental campaign with data gathered by a proprietary UWB localization system.

Keywords: Gauss–Newton algorithm; Isolation forest; Levenberg–Marquardt algorithm; UWB; anchor self-localization; antenna delay; localization; outlier detection.

MeSH terms

  • Algorithms
  • Computers
  • Sports*
  • Technology
  • Wireless Technology*

Grants and funding

This research was supported by Tracking4Fun S.r.l. under private funding.