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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Eurocon_final_v2.pdf | 1.53 MB | Adobe PDF | View/Open |
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