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Dil, B.J. and Havinga, P.J.M. (2010) On the Calibration and Performance of RSS-based Localization Methods. In: Internet of Things, IOT 2010, 29 Nov - 1 Dec 2010 , Tokyo, Japan. pp. 1-8. IEEE Computer Society. ISBN 978-1-4244-7413-4
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Official URL: http://dx.doi.org/10.1109/IOT.2010.5678435
This paper analyzes the performance of several Received Signal Strength (RSS) based localization methods as a function of the calibration effort, hence as a function of deployment and maintenance costs. The deployment and maintenance costs determine the scalability and thus the applicability of a localization algorithm, and this is still a topic of research. This paper analyzes and compares the best available localization algorithms of the following localization methods: fingerprinting-, range- and proximity-based localization. An extensive amount of RSS measurements, performed in a realistic indoor environment show that range-based algorithms outperform fingerprinting and proximity-based localization algorithms when there is a limited amount of calibration measurements available. In that case, range-based algorithms have ~30% smaller errors, ~1.3 meter compared to ~1.9 meter. Our measurements show that fingerprinting-based algorithms approximate the performance of range-based algorithms as the number of calibration measurements increases from 1 to 80.
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