In:
ISPRS International Journal of Geo-Information, MDPI AG, Vol. 9, No. 12 ( 2020-12-01), p. 714-
Abstract:
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.
Type of Medium:
Online Resource
ISSN:
2220-9964
Language:
English
Publisher:
MDPI AG
Publication Date:
2020
detail.hit.zdb_id:
2655790-3
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