Abstract
This letter presents an extended Kalman filtering algorithm for position tracking with a radio map consisting of received signal strength (RSS) observations by a single device at known positions. The proposed algorithm is based on a time-varying RSS model, introduced in this letter, to track the position of a device and the RSS variation arising from device heterogeneity and environmental changes. The superiority of the proposed algorithm over the existing algorithms is validated with simulations and a real experiment.
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