Enhanced triangulation method for positioning of moving devices

This paper proposes an improvement of triangulation methods for a moving device and evaluates the enhancement in detailed simulation experiments for the example use-case of an indoor scenario utilizing Bluetooth technology. Accurate positioning methods using short-range communication technologies are increasingly important for various applications including tracking as well as more general context-sensitive networking approaches and applications. Relevant positioning algorithms include triangulation based on measured link properties to several Base Stations. In the case of moving devices, accurate positioning becomes very challenging for two main reasons. On one hand measurement errors and changing propagation conditions require probabilistic approaches. On the other hand, due to the movement of the devices, the triangulation method based on multiple measurements becomes less accurate, since they cannot be obtained at exactly the same time instant. To mitigate these constraints, the proposed method is based on movement prediction. Keywords— Positioning, Movement Prediction, Triangulation, Bluetooth

[1]  David K. Y. Yau,et al.  On the effectiveness of movement prediction to reduce energy consumption in wireless communication , 2003, IEEE Transactions on Mobile Computing.

[2]  William G. Scanlon,et al.  Stepwise Algorithms for Improving the Accuracy of Both Deterministic and Probabilistic Methods in WLAN-based Indoor User Localisation , 2004, Int. J. Wirel. Inf. Networks.

[3]  Henry Tirri,et al.  A Probabilistic Approach to WLAN User Location Estimation , 2002, Int. J. Wirel. Inf. Networks.

[4]  Kyandoghere Kyamakya,et al.  An Indoor Bluetooth-Based Positioning System: Concept, Implementation and Experimental Evaluation , 2003, International Conference on Wireless Networks.

[5]  Chris R. Drane Positioning Systems: A Unified Approach , 1992 .

[6]  Vincent K. N. Lau,et al.  The Mobile Radio Propagation Channel , 2007 .

[7]  Moustafa Youssef,et al.  WLAN location determination via clustering and probability distributions , 2003, Proceedings of the First IEEE International Conference on Pervasive Computing and Communications, 2003. (PerCom 2003)..

[8]  Damià Vidal Performance simulation on a multitarget radial remote-positioning system , 1995, MASCOTS '95. Proceedings of the Third International Workshop on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems.

[9]  István Z. Kovács,et al.  Accuracy and timing aspects of location information based on signal-strength measurements in Bluetooth , 2005, 2005 IEEE 16th International Symposium on Personal, Indoor and Mobile Radio Communications.