NDLI: Near Relation-Based Indoor Positioning Method under Sparse Wi-Fi Fingerprints

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Near Relation-Based Indoor Positioning Method under Sparse Wi-Fi Fingerprints

Content Provider	MDPI
Author	Wang, Yankun Guo, Renzhong Wang, Weixi Li, Xiao Ming Tang, Shengjun Zhang, Wei Wang, Luyao Chen, Liang Li, You Xiu, Wenqun
Copyright Year	2020
Description	Indoor positioning is of great importance in the era of mobile computing. Currently, considerable focus has been on RSS-based locations because they can provide position information without additional equipment. However, this method suffers from two challenges: (1) fingerprint ambiguity and (2) labour-intensive fingerprint collection. To overcome these drawbacks, we provide a near relation-based indoor positioning method under a sparse Wi-Fi fingerprint. To effectively obtain the fingerprint database, certain interpolation methods are used to enrich sparse Wi-Fi fingerprints. A near relation boundary is provided, and Wi-Fi fingerprints are constrained to this region to reduce fingerprint ambiguity, which can also improve the efficiency of fingerprint matching. Extensive experiments show that the kriging interpolation method performs well, and a positioning accuracy of 2.86 m can be achieved with a near relation under a 1 m interpolation density.
Starting Page	714
e-ISSN	22209964
DOI	10.3390/ijgi9120714
Journal	ISPRS International Journal of Geo-Information
Issue Number	12
Volume Number	9
Language	English
Publisher	MDPI
Publisher Date	2020-12-01
Access Restriction	Open
Subject Keyword	ISPRS International Journal of Geo-Information Isprs International Journal of Geo-information Industrial Engineering Indoor Positioning Near Relation Sparse Wi-fi Fingerprint Fingerprint Ambiguity
Content Type	Text
Resource Type	Article

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