Wireless localization with diffusion maps

In the Wireless Localization Matching Problem (WLMP) the challenge is to match pieces of equipment with a set of candidate locations based on wireless signal measurements taken by the pieces of equipment. This challenge is complicated by the noise that is inherent in wireless signal measurements. He...

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Published inScientific reports Vol. 10; no. 1; p. 20655
Main Authors Ghafourian, Amin, Georgiou, Orestis, Barter, Edmund, Gross, Thilo
Format Journal Article
LanguageEnglish
Published England Nature Publishing Group 26.11.2020
Nature Publishing Group UK
Subjects
Algorithms
Computer applications
Costs
Diffusion
Embedding
Internet of Things
Localization
Methods
Noise
Sensors
Wireless networks
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Summary:In the Wireless Localization Matching Problem (WLMP) the challenge is to match pieces of equipment with a set of candidate locations based on wireless signal measurements taken by the pieces of equipment. This challenge is complicated by the noise that is inherent in wireless signal measurements. Here we propose the use of diffusion maps, a manifold learning technique, to obtain an embedding of positions and equipment coordinates in a space that enables coordinate comparison and reliable evaluation of assignment quality at very low computational cost. We show that the mapping is robust to noise and using diffusion maps allows for accurate matching in a realistic setting. This suggests that the diffusion-map-based approach could significantly increase the accuracy of wireless localization in applications.
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ISSN:2045-2322
2045-2322
DOI:10.1038/s41598-020-77695-7