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2016
Conference Paper
Titel
Analysis and evaluation of a particle filter for Wi-Fi azimuth and position tracking
Abstract
A tracking algorithm for position and azimuth estimation based on Wi-Fi fingerprinting with directional antennas is analyzed and evaluated. A particle filter is used for fusing received signal strength of Wi-Fi with sensor readings of an inertial measurement unit, which is combined with pedestrian dead reckoning. Two setups for different application scenarios were developed and evaluated in an industry-like environment. The proposed approach reduces position error by up to 58% in sub-optimal scenarios, such as fewer available access points or a single directional antenna. In addition, the estimation of azimuth of the subject improves up to 64%.