ZigBee based indoor localization with particle filter estimation

Highly-functional mobile devices, such a smart phone, have appeared. Location based services of the mobile devices are assimilated in a variety of ways. Then, Indoor localization sensor is necessary to access the location based services seamlessly. This paper researched the performance of indoor localization with ZigBee based particle filter. This paper showed this method can localize a resting target within 2.0 meter accuracy and can localize a moving target with an area levels localization. ZigBee based particle filter can be one of some options for location based services in indoor spaces.

[1]  Imrich Chlamtac,et al.  Indoor location tracking using RSSI readings from a single Wi-Fi access point , 2007, Wirel. Networks.

[2]  Jing Liu,et al.  Survey of Wireless Indoor Positioning Techniques and Systems , 2007, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[3]  Shinsuke Hara,et al.  RSSI-based Localization without a Prior Knowledge of Channel Model Parameters , 2008, Int. J. Wirel. Inf. Networks.

[4]  Nando de Freitas,et al.  Sequential Monte Carlo Methods in Practice , 2001, Statistics for Engineering and Information Science.

[5]  Yu Hen Hu,et al.  Maximum likelihood multiple-source localization using acoustic energy measurements with wireless sensor networks , 2005, IEEE Transactions on Signal Processing.

[6]  Paramvir Bahl,et al.  RADAR: an in-building RF-based user location and tracking system , 2000, Proceedings IEEE INFOCOM 2000. Conference on Computer Communications. Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies (Cat. No.00CH37064).

[7]  G. Kitagawa.  Monte Carlo Filter and Smoother for Non-Gaussian Nonlinear State Space Models , 1996 .

[8]  R.L. Moses,et al.  Locating the nodes: cooperative localization in wireless sensor networks , 2005, IEEE Signal Processing Magazine.

[9]  Jan M. Rabaey,et al.  PicoRadio Supports Ad Hoc Ultra-Low Power Wireless Networking , 2000, Computer.

[10]  Alfred O. Hero,et al.  Locating the Nodes , 2005 .

[11]  Gergely V. Záruba,et al.  A Bayesian sampling approach to in-door localization of wireless devices using received signal strength indication , 2005, Third IEEE International Conference on Pervasive Computing and Communications.

[12]  François Marx,et al.  Advanced Integration of WiFi and Inertial Navigation Systems for Indoor Mobile Positioning , 2006, EURASIP J. Adv. Signal Process..