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2013 International Conference on Information Networking (ICOIN)
Indoor localization improvement via adaptive RSS fingerprinting database
Bangkok Thailand
January 28-January 30
ISBN: 978-1-4673-5740-1
Kamol Kaemarungsi, Embedded System Technology Laboratory (EST) National Electronics and Computer Technology Center (NECTEC) Pathumthani, Thailand
In location fingerprinting based indoor positioning system, received signal strength (RSS) indications from a set of Wi-Fi access points are used as a unique fingerprint to identify a specific location. However these RSS fingerprints may become outdated when there are unanticipated environmental changes. Re-measuring RSS fingerprints for all locations to maintain an up-to-date RSS database incurs high operational cost, which is impractical in dynamically changed environment. In this paper, we propose a method to estimate the RSS fingerprint of a specific location from a set of neighboring re-measured RSS fingerprints, called “feedbacks”. The proposed method searches for new feedbacks and some necessary old RSS fingerprints in the cut-off area and then applies plane-interpolation to calculate the new RSS fingerprint for a specific location. Based on simulation results, about 5% of re-measured RSS feedbacks are required to satisfy 80% of positioning correctness in the simulated 30×30 m2 area.
Index Terms:
feedback,Location estimation,Wi-Fi fingerprint,adaptive RSS fingerprint,plane-interpolation
Citation:
Kamol Kaemarungsi, "Indoor localization improvement via adaptive RSS fingerprinting database," icoin, pp.412-416, 2013 International Conference on Information Networking (ICOIN), 2013
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