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
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.
