6th International ICST Conference on Communications and Networking in China

Research Article

Auxiliary Particle Filter-Based WLAN Indoor Tracking Algorithm

  • @INPROCEEDINGS{10.1109/ChinaCom.2011.6158225,
        author={Junyi Han and Lin Ma and Yubin Xu and Zhian Deng},
        title={Auxiliary Particle Filter-Based WLAN Indoor Tracking Algorithm},
        proceedings={6th International ICST Conference on Communications and Networking in China},
        publisher={IEEE},
        proceedings_a={CHINACOM},
        year={2012},
        month={3},
        keywords={apf pf wlan indooor tracking fingerprinting technology},
        doi={10.1109/ChinaCom.2011.6158225}
    }
    
  • Junyi Han
    Lin Ma
    Yubin Xu
    Zhian Deng
    Year: 2012
    Auxiliary Particle Filter-Based WLAN Indoor Tracking Algorithm
    CHINACOM
    IEEE
    DOI: 10.1109/ChinaCom.2011.6158225
Junyi Han1,*, Lin Ma1, Yubin Xu1, Zhian Deng1
  • 1: Harbin Institute of Technology
*Contact email: hanjunyi88@163.com

Abstract

The particle filter (PF) has been implemented for location tracking in Wireless Local Area Network (WLAN) based indoor positioning system. However, the traditional PF technology is based on the sampling importance resampling (SIR), which has the inherent blindness. Therefore, its tracking performance in WLAN indoor environment is degraded. The auxiliary particle filter (APF) can solve this problem very well by making use of the current observation information during the production of new particles, so this paper employs the auxiliary particle filter (APF) for location tracking in WLAN fingerprinting positioning system to improve the WLAN indoor tracking performance. In the simulation, the weighted k-nearest neighbors method (WKNN) is chosen as the fingerprinting positioning algorithm. Simulation results show that APF based tracking algorithm performs better than PF based tracking algorithm. The APF based WLAN indoor tracking algorithm decreases the mean tracking error by 7.7% and 26.9% than PF based tracking algorithm and WKNN algorithm respectively.