Indoor Localization Accuracy Estimation from Fingerprint Data

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  • Artyom Nikitin
  • Christos Laoudias
  • Georgios Chatzimilioudis
  • Panagiotis Karras
  • Demetrios Zeinalipour-Yazti

Abstract

The demand for indoor localization services has led to the development of techniques that create a Fingerprint Map (FM) of sensor signals (e.g., magnetic, Wi-Fi, bluetooth) at designated positions in an indoor space and then use FM as a reference for subsequent localization tasks. With such an approach, it is crucial to assess the quality of the FM before deployment, in a manner disregarding data origin and at any location of interest, so as to provide deployment staff with the information on the quality of localization. Even though FM-based localization algorithms usually provide accuracy estimates during system operation (e.g., visualized as uncertainty circle or ellipse around the user location), they do not provide any information about the expected accuracy before the actual deployment of the localization service. In this paper, we develop a novel framework for quality assessment on arbitrary FMs coined ACCES. Our framework comprises a generic interpolation method using Gaussian Processes (GP), upon which a navigability score at any location is derived using the Cramer-Rao Lower Bound (CRLB). Our approach does not rely on the underlying physical model of the fingerprint data. Our extensive experimental study with magnetic FMs, comparing empirical localization accuracy against derived bounds, demonstrates that the navigability score closely matches the accuracy variations users experience.
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Detaljer

The demand for indoor localization services has led to the development of techniques that create a Fingerprint Map (FM) of sensor signals (e.g., magnetic, Wi-Fi, bluetooth) at designated positions in an indoor space and then use FM as a reference for subsequent localization tasks. With such an approach, it is crucial to assess the quality of the FM before deployment, in a manner disregarding data origin and at any location of interest, so as to provide deployment staff with the information on the quality of localization. Even though FM-based localization algorithms usually provide accuracy estimates during system operation (e.g., visualized as uncertainty circle or ellipse around the user location), they do not provide any information about the expected accuracy before the actual deployment of the localization service. In this paper, we develop a novel framework for quality assessment on arbitrary FMs coined ACCES. Our framework comprises a generic interpolation method using Gaussian Processes (GP), upon which a navigability score at any location is derived using the Cramer-Rao Lower Bound (CRLB). Our approach does not rely on the underlying physical model of the fingerprint data. Our extensive experimental study with magnetic FMs, comparing empirical localization accuracy against derived bounds, demonstrates that the navigability score closely matches the accuracy variations users experience.
OriginalsprogEngelsk
Titel18th IEEE International Conference on Mobile Data Management (MDM)
Antal sider10
ForlagIEEE
Publikationsdato31 maj 2017
ISBN (Elektronisk)978-1-5386-3932-0
DOI
StatusUdgivet - 31 maj 2017
PublikationsartForskning
Peer reviewJa
Begivenhed18th IEEE International Conference on Mobile Data Management - KAIST, Daejeon, Sydkorea
Varighed: 29 maj 20171 jun. 2017
Konferencens nummer: 18
http://mdmconferences.org/mdm2017/

Konference

Konference18th IEEE International Conference on Mobile Data Management
Nummer18
LokationKAIST
LandSydkorea
ByDaejeon
Periode29/05/201701/06/2017
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