Poster Abstract: Machine Learning-based Models for Phase-Difference-of-Arrival Measurements Using Ultra-Wideband Transceivers

Leo Botler, Milot Gashi, Konrad Diwold, Kay Romer

Publikation: Beitrag in Buch/Bericht/KonferenzbandBeitrag in einem KonferenzbandBegutachtung

Abstract

Ultra-wideband technology is applied for indoor positioning systems and achieves a position accuracy in the order of decimeters. A trending approach in this context relies on combined angle-of-arrival and time-of-flight measurements, and enables localization using a single anchor, thereby reducing infrastructure overhead. Although analytical models already exist for Ultra-wideband-based distance estimation using time-of-flight, no model has been proposed for its angle-of-arrival counterpart. In this paper we cover this gap by investigating the use of 4 different machine learning regressors to generate such models. The models were trained with data from real-world experiments performed with commercial off-the-shelf Ultra-wideband modules. The models can be easily integrated in simulators, facilitating and even enabling the evaluation of scalable positioning systems using this technology. Among the tested regressors, the random forest regressor presented the best fit to the experimental data, with MAE of the 'mean' parameter of 8°.

Originalspracheenglisch
TitelProceedings - 21st ACM/IEEE International Conference on Information Processing in Sensor Networks, IPSN 2022
Herausgeber (Verlag)Institute of Electrical and Electronics Engineers
Seiten517-518
Seitenumfang2
ISBN (elektronisch)9781665496247
DOIs
PublikationsstatusVeröffentlicht - 2022
Veranstaltung21st ACM/IEEE International Conference on Information Processing in Sensor Networks, IPSN 2022 - Virtual, Online, Italien
Dauer: 4 Mai 20226 Mai 2022

Publikationsreihe

NameProceedings - 21st ACM/IEEE International Conference on Information Processing in Sensor Networks, IPSN 2022

Konferenz

Konferenz21st ACM/IEEE International Conference on Information Processing in Sensor Networks, IPSN 2022
Land/GebietItalien
OrtVirtual, Online
Zeitraum4/05/226/05/22

ASJC Scopus subject areas

  • Computernetzwerke und -kommunikation
  • Hardware und Architektur
  • Information systems
  • Informationssysteme und -management

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