Hybrid Multipath Assisted Positioning and Fingerprinting Using Transformer Models

Markus Ulmschneider, Christian Gentner, and Armin Dammann

Abstract:	Multipath assisted positioning exploits the spatial information contained in wireless radio signals for localizing a receiver. While such schemes are computationally very complex, they can be used in the offline phase of a fingerprinting scheme. We have presented previously such a fingerprinting scheme, where the fingerprints are channel features, and their locations are estimated with a multipath assisted positioning scheme in the offline phase. The fingerprints and their locations are used to train a mixture density network (MDN). Within this paper, we investigate the benefit of a modern transformer model compared to a MDN.
Published in:	Proceedings of the 37th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2024) September 16 - 20, 2024 Hilton Baltimore Inner Harbor Baltimore, Maryland
Pages:	1878 - 1884
Cite this article:	Ulmschneider, Markus, Gentner, Christian, Dammann, Armin, "Hybrid Multipath Assisted Positioning and Fingerprinting Using Transformer Models," Proceedings of the 37th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2024), Baltimore, Maryland, September 2024, pp. 1878-1884. https://doi.org/10.33012/2024.19878
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