4th International ICST Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services

Research Article

Using Weighted Graphs for Computationally Efficient WLAN Location Determination

  • @INPROCEEDINGS{10.1109/MOBIQ.2007.4451008,
        author={Ren\^{e} Hansen and Bent Thomsen},
        title={Using Weighted Graphs for Computationally Efficient WLAN Location Determination},
        proceedings={4th International ICST Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services},
        publisher={IEEE},
        proceedings_a={MOBIQUITOUS},
        year={2008},
        month={2},
        keywords={Application software  Bluetooth  Coordinate measuring machines  Fingerprint recognition  Global Positioning System  Indoor environments  Land mobile radio cellular systems  Mobile computing  Mobile handsets  Wireless LAN},
        doi={10.1109/MOBIQ.2007.4451008}
    }
    
  • René Hansen
    Bent Thomsen
    Year: 2008
    Using Weighted Graphs for Computationally Efficient WLAN Location Determination
    MOBIQUITOUS
    IEEE
    DOI: 10.1109/MOBIQ.2007.4451008
René Hansen1,*, Bent Thomsen1,*
  • 1: Department of Computer Science Aalborg University Fredrik Bajers Vej 7E, DK-9220 Aalborg Øst, Denmark
*Contact email: rhansen@cs.aau.dk, bt@cs.aau.dk

Abstract

Indoor location-based services hold promise for a multitude of valuable services, but require micro-detailed georeferencing not achievable with “outdoor” technologies such as GPS and cellular networks. A widely used technique for accurate indoor positioning is location fingerprinting which makes use of existing WLAN infrastructures. The technique consists of building a radio map of signal strength measurements which is searched to determine a position estimate. While the fingerprinting technique has produced good positioning accuracy results, the technique incurs a substantial computational burden for large buildings and is thus problematic for tracking users in real time on processor-constrained mobile devices. In this paper we present a technique for improving the computational efficiency of the fingerprinting technique such that location determination becomes tractable on a mobile device. The technique is based on a graph-modeling of the physical environment and works by restricting the search space to positions that are possible to reach from a previously estimated position. The technique is general in that it can be applied in conjunction with any positioning algorithm, and a positive side effect is that it may enhance the positioning accuracy of the system.