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Evaluating GPS Data in Indoor EnvironmentsMOTTE, H. , WYFFELS, J. , DE STRYCKER, L. , GOEMAERE, J.-P.
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context-aware services, Global Positioning System, indoor environments, radiowave propagation, satellite navigation systems
indoor(8), strycker(6), sensor(5), navigation(5), localization(5), goemaere(5), wyffels(4), networks(4), location(4), local(4)
Blue keywords are present in both the references section and the paper title.
About this article
Date of Publication: 2011-08-31
Volume 11, Issue 3, Year 2011, On page(s): 25 - 28
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2011.03004
Web of Science Accession Number: 000296186700004
SCOPUS ID: 80055087410
With the latest generation of ultra-sensitive GPS-receivers, satellite signals can often be picked up even indoors, resulting in (inaccurate) indoor GPS-localization. A covered position will therefore no longer be characterized by the absence of satellite signals, creating the need for another way of categorizing this data as potentially inaccurate. This paper describes the use of GPS-based localization in an indoor environment. Only high level, generally available, GPS-data (NMEA-0183 GNSS-subset) are taken into account. Applications of ubiquitous location awareness, where the use of several RTLS (Real Time Location System) combinations is feasible, may benefit from this information to discriminate between GPS and other available localization data. A quality indicating parameter is readily available in GPS-data; the DOP (Dilution Of Precision) data field, which indicates the accuracy of the GPS localization based on the current satellite geometry. However since in indoor environments the roof and possible overlying floors often cause more signal attenuation compared to (outer) walls or windows, the probability of a better reception of 'low' orbiting satellite signals increases, giving rise to an unjustified good horizontal DOP value. Standard NMEA-0183 GPS strings are therefore analyzed in search of other indicators for malicious GPS-data.
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 From Coarse to Fine: Two-Stage Indoor Localization with Multisensor Fusion, Zhang, Li, Bao, Jinhui, Xu, Yi, Wang, Qiuyu, Xu, Jingao, Li, Danyang, Tsinghua Science and Technology, ISSN 1007-0214, Issue 3, Volume 28, 2023.
Digital Object Identifier: 10.26599/TST.2022.9010029 [CrossRef]
 Implementation of a WiFi-based indoor location system on a mobile device for a university area, Fernandez, Dennis Nunez, 2019 IEEE XXVI International Conference on Electronics, Electrical Engineering and Computing (INTERCON), ISBN 978-1-7281-3646-2, 2019.
Digital Object Identifier: 10.1109/INTERCON.2019.8853556 [CrossRef]
 Multi-Region Indoor Localization Based on WVP System, Zhang, Li, Xu, Yi, Bao, Jinhui, Wang, Qiuyu, Xu, Jingao, Li, Danyang, Yang, Yaodong, Zhang, Min, 2021 IEEE 27th International Conference on Parallel and Distributed Systems (ICPADS), ISBN 978-1-6654-0878-3, 2021.
Digital Object Identifier: 10.1109/ICPADS53394.2021.00102 [CrossRef]
 RSSI - WIFI Based Indoor Position Tracking System Using Support Vector Machine (SVM), Irsan, Ferdian A.S., Aminah, Nina Siti, Djamal, Mitra, 2022 International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME), ISBN 978-1-6654-7095-7, 2022.
Digital Object Identifier: 10.1109/ICECCME55909.2022.9988134 [CrossRef]
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Stefan cel Mare University of Suceava, Romania
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