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http://dx.doi.org/10.5302/J.ICROS.2015.15.0149

Indoor Localization Using Unscented Kalman/FIR Hybrid Filter  

Pak, Jung Min (School of Electrical Engineering, Korea University)
Ahn, Choon Ki (School of Electrical Engineering, Korea University)
Lim, Myo Taeg (School of Electrical Engineering, Korea University)
Song, Moon Kyou (Department of Electronics Convergence Engineering, Wonkwang University)
Publication Information
Journal of Institute of Control, Robotics and Systems / v.21, no.11, 2015 , pp. 1057-1063 More about this Journal
Abstract
This paper proposes a new nonlinear filtering algorithm that combines the unscented Kalman filter (UKF) and the finite impulse response (FIR) filter. The proposed filter is called the unscented Kalman/FIR hybrid filter (UKFHF). In the UKFHF algorithm, the UKF is used as the main filter, which produces state estimates under ideal conditions. When failures of the UKF are detected, the FIR filter is operated. Using the output of the FIR filter, the UKF is reset and rebooted. In this way, the UKFHF recovers from failures. The proposed UKFHF is applied to indoor human localization using wireless sensor networks. Through simulations, the performance of the UKFHF is demonstrated in comparison with that of the UKF.
Keywords
indoor localization; finite impulse response (FIR) filter; unscented Kalman filter; unscented Kalman/FIR hybrid filter;
Citations & Related Records
Times Cited By KSCI : 4  (Citation Analysis)
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