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RSS Indoor Localization Based on a Single Access Point

This research work investigates how RSS information fusion from a single, multi-antenna access point (AP) can be used to perform device localization in indoor RSS based localization systems. The proposed approach demonstrates that different RSS values can be obtained by carefully modifying each AP a...

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Detalles Bibliográficos
Autores principales: Kokkinis, Akis, Kanaris, Loizos, Liotta, Antonio, Stavrou, Stavros
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6749368/
https://www.ncbi.nlm.nih.gov/pubmed/31461834
http://dx.doi.org/10.3390/s19173711
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author Kokkinis, Akis
Kanaris, Loizos
Liotta, Antonio
Stavrou, Stavros
author_facet Kokkinis, Akis
Kanaris, Loizos
Liotta, Antonio
Stavrou, Stavros
author_sort Kokkinis, Akis
collection PubMed
description This research work investigates how RSS information fusion from a single, multi-antenna access point (AP) can be used to perform device localization in indoor RSS based localization systems. The proposed approach demonstrates that different RSS values can be obtained by carefully modifying each AP antenna orientation and polarization, allowing the generation of unique, low correlation fingerprints, for the area of interest. Each AP antenna can be used to generate a set of fingerprint radiomaps for different antenna orientations and/or polarization. The RSS fingerprints generated from all antennas of the single AP can be then combined to create a multi-layer fingerprint radiomap. In order to select the optimum fingerprint layers in the multilayer radiomap the proposed methodology evaluates the obtained localization accuracy, for each fingerprint radio map combination, for various well-known deterministic and probabilistic algorithms (Weighted k-Nearest-Neighbor—WKNN and Minimum Mean Square Error—MMSE). The optimum candidate multi-layer radiomap is then examined by calculating the correlation level of each fingerprint pair by using the “Tolerance Based—Normal Probability Distribution (TBNPD)” algorithm. Both steps take place during the offline phase, and it is demonstrated that this approach results in selecting the optimum multi-layer fingerprint radiomap combination. The proposed approach can be used to provide localisation services in areas served only by a single AP.
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spelling pubmed-67493682019-09-27 RSS Indoor Localization Based on a Single Access Point Kokkinis, Akis Kanaris, Loizos Liotta, Antonio Stavrou, Stavros Sensors (Basel) Article This research work investigates how RSS information fusion from a single, multi-antenna access point (AP) can be used to perform device localization in indoor RSS based localization systems. The proposed approach demonstrates that different RSS values can be obtained by carefully modifying each AP antenna orientation and polarization, allowing the generation of unique, low correlation fingerprints, for the area of interest. Each AP antenna can be used to generate a set of fingerprint radiomaps for different antenna orientations and/or polarization. The RSS fingerprints generated from all antennas of the single AP can be then combined to create a multi-layer fingerprint radiomap. In order to select the optimum fingerprint layers in the multilayer radiomap the proposed methodology evaluates the obtained localization accuracy, for each fingerprint radio map combination, for various well-known deterministic and probabilistic algorithms (Weighted k-Nearest-Neighbor—WKNN and Minimum Mean Square Error—MMSE). The optimum candidate multi-layer radiomap is then examined by calculating the correlation level of each fingerprint pair by using the “Tolerance Based—Normal Probability Distribution (TBNPD)” algorithm. Both steps take place during the offline phase, and it is demonstrated that this approach results in selecting the optimum multi-layer fingerprint radiomap combination. The proposed approach can be used to provide localisation services in areas served only by a single AP. MDPI 2019-08-27 /pmc/articles/PMC6749368/ /pubmed/31461834 http://dx.doi.org/10.3390/s19173711 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Kokkinis, Akis
Kanaris, Loizos
Liotta, Antonio
Stavrou, Stavros
RSS Indoor Localization Based on a Single Access Point
title RSS Indoor Localization Based on a Single Access Point
title_full RSS Indoor Localization Based on a Single Access Point
title_fullStr RSS Indoor Localization Based on a Single Access Point
title_full_unstemmed RSS Indoor Localization Based on a Single Access Point
title_short RSS Indoor Localization Based on a Single Access Point
title_sort rss indoor localization based on a single access point
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6749368/
https://www.ncbi.nlm.nih.gov/pubmed/31461834
http://dx.doi.org/10.3390/s19173711
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