Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.12188/22641
Title: Indoor localization of unmanned aerial vehicles based on RSSI
Authors: Trivodaliev, Kire 
Risteska Stojkoska, Biljana
Palikrushev, Jordan
Kalajdziski, Slobodan 
Keywords: indoor localization; positioning; unmanned aerial vehicle; multidimensional scaling; weighted centroid
Issue Date: 6-Jul-2017
Publisher: IEEE
Conference: IEEE EUROCON 2017-17th International Conference on Smart Technologies
Abstract: Nowadays, finding the Unmanned Aerial Vehicle (UAV) position in the absence of GPS is attractive and challenging problem in the research community. In this paper, we present a novel algorithm for mini UAV indoor localization based on distance measurements between the UAV and the existing infrastructure consisting of WiFi Access Points. Our algorithm uses two well-known techniques from the literature: Multi-dimensional Scaling (MDS) and Weighted Centroid Localization (WCL). Through extensive simulations we have shown that our algorithm is very suitable for indoor localization of mini UAVs. For small radio-range error, our algorithm exhibits a small localization error of less than 5% of the radio range.
URI: http://hdl.handle.net/20.500.12188/22641
Appears in Collections:Faculty of Computer Science and Engineering: Conference papers

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