NDLI: Robustness in Fingerprinting-Based Indoor Positioning Systems

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Robustness in Fingerprinting-Based Indoor Positioning Systems

Content Provider	Semantic Scholar
Author	Fang, Shih-Hau
Copyright Year	2018
Abstract	Indoor positioning systems have received increasing attention for supporting location-based services in indoor environments. Received signal strength (RSS), mostly utilized in Wi-Fi fingerprinting systems, is known to be unreliable due to two reasons: orientation mismatch and variations in hardware. This chapter introduces an approach based on histogram equalization to compensate for orientation mismatch in robust Wi-Fi localization. The proposed method involves converting the temporal-spatial radio signal strength into a reference function (i.e., equalizing the histogram). This chapter also introduces an enhanced positioning feature, which is called delta-fused principal strength, to enhance the robustness of Wi-Fi localization against the problem of heterogeneous hardware. This algorithm computes the pairwise delta RSS and then integrates with RSS using principal component analysis. The proposed methods effectively and efficiently improve the robustness of location estimation in the presence of mismatch orientation and hardware variations, respectively.
Starting Page	88
Ending Page	141
Page Count	54
File Format	PDF HTM / HTML
DOI	10.4018/978-1-5225-3528-7.ch003
Alternate Webpage(s)	https://www.igi-global.com/viewtitlesample.aspx?id=195714&ptid=181077&t=robustness+in+fingerprinting-based+indoor+positioning+systems
Alternate Webpage(s)	https://doi.org/10.4018/978-1-5225-3528-7.ch003
Language	English
Access Restriction	Open
Content Type	Text
Resource Type	Article

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