Indoor localization using unscented Kalman/FIR hybrid filter

Jung Min Pak; Choon Ki Ahn; Myo Taeg Lim; Moon Kyou Song

doi:10.5302/J.ICROS.2015.15.0149

Indoor localization using unscented Kalman/FIR hybrid filter

Jung Min Pak, Choon Ki Ahn, Myo Taeg Lim, Moon Kyou Song

Research output: Contribution to journal › Article › peer-review

2 Citations (Scopus)

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.

Original language	English
Pages (from-to)	1057-1063
Number of pages	7
Journal	Journal of Institute of Control, Robotics and Systems
Volume	21
Issue number	11
DOIs	https://doi.org/10.5302/J.ICROS.2015.15.0149
Publication status	Published - 2015 Nov 1

Keywords

Finite impulse response (FIR) filter
Indoor localization
Unscented Kalman filter
Unscented Kalman/FIR hybrid filter

ASJC Scopus subject areas

Software
Control and Systems Engineering
Applied Mathematics

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10.5302/J.ICROS.2015.15.0149

Cite this

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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.",

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AB - 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.

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Indoor localization using unscented Kalman/FIR hybrid filter

Abstract

Keywords

ASJC Scopus subject areas

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