Journal of Institute of Control, Robotics and Systems (제어로봇시스템학회논문지)

Institute of Control, Robotics and Systems (제어로봇시스템학회)
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Indoor Localization Using Unscented Kalman/FIR Hybrid Filter

언센티드 칼만/FIR 하이브리드 필터를 이용한 실내 위치 추정

  • 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)
  • 박정민 (고려대학교 전기전자공학부) ;
  • 안춘기 (고려대학교 전기전자공학부) ;
  • 임묘택 (고려대학교 전기전자공학부) ;
  • 송문규 (원광대학교 전자융합공학과)
  • Received : 2015.08.17
  • Accepted : 2015.10.01
  • Published : 2015.11.01
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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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References

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