Geometric-based KNN localization using sensor dissimilarity information | IEEE Conference Publication | IEEE Xplore

Geometric-based KNN localization using sensor dissimilarity information

Publisher: IEEE

Abstract:

Location fingerprinting is a range-free approach to GPS-free localization. Conventionally, the fingerprint space is defined as a feature vector space where a fingerprint ...View more

Abstract:

Location fingerprinting is a range-free approach to GPS-free localization. Conventionally, the fingerprint space is defined as a feature vector space where a fingerprint is a vector of location-sensitive measurements associated with a location. However, in practice, it is hard to find a quality feature space that is robust to device heterogeneity and environment and infrastructure dynamics. This paper advocates a fundamentally different model where a fingerprint is defined as a dissimilarity measurement associated with a pair of locations and proposes a localization approach based on geometric embedding.
Date of Conference: 08-13 October 2017
Date Added to IEEE Xplore: 15 February 2018
ISBN Information:
Electronic ISSN: 2166-9589
Publisher: IEEE
Conference Location: Montreal, QC, Canada

References

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