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Open AccessArticle

NLOS Identification and Mitigation Using Low-Cost UWB Devices

Universidade da Coruña (University of A Coruña), CITIC Research Center, Campus de Elviña, 15071 A Coruña, Spain
Author to whom correspondence should be addressed.
Sensors 2019, 19(16), 3464;
Received: 13 June 2019 / Revised: 12 July 2019 / Accepted: 6 August 2019 / Published: 8 August 2019
(This article belongs to the Special Issue Sensors Localization in Indoor Wireless Networks)
Indoor location systems based on ultra-wideband (UWB) technology have become very popular in recent years following the introduction of a number of low-cost devices on the market capable of providing accurate distance measurements. Although promising, UWB devices also suffer from the classic problems found when working in indoor scenarios, especially when there is no a clear line-of-sight (LOS) between the emitter and the receiver, causing the estimation error to increase up to several meters. In this work, machine learning (ML) techniques are employed to analyze several sets of real UWB measurements, captured in different scenarios, to try to identify the measurements facing non-line-of-sight (NLOS) propagation condition. Additionally, an ulterior process is carried out to mitigate the deviation of these measurements from the actual distance value between the devices. The results show that ML techniques are suitable to identify NLOS propagation conditions and also to mitigate the error of the estimates when there is LOS between the emitter and the receiver. View Full-Text
Keywords: UWB; machine learning; NLOS identification UWB; machine learning; NLOS identification
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Barral, V.; Escudero, C.J.; García-Naya, J.A.; Maneiro-Catoira, R. NLOS Identification and Mitigation Using Low-Cost UWB Devices. Sensors 2019, 19, 3464.

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