An Indoor Positioning System Based on Probabilistic Model with ZigBee Sensor Networks

Junpei Tsuji; Hidenori Kawamura; Keiji Suzuki; Takeshi Ikeda; Akio Sashima; Koichi Kurumatani

doi:10.20965/jaciii.2010.p0669

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JACIII Vol.14 No.6 pp. 669-676

doi: 10.20965/jaciii.2010.p0669

(2010)

Paper:

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An Indoor Positioning System Based on Probabilistic Model with ZigBee Sensor Networks

Junpei Tsuji^*,***, Hidenori Kawamura^*,***, Keiji Suzuki^,,
Takeshi Ikeda^,, Akio Sashima^,,
and Koichi Kurumatani^,***

^*Laboratory of Harmonious Systems Engineering, Hokkaido University, Sapporo, Japan

^**National Institute of Advanced Industrial Science and Technology (AIST), Tokyo, Japan

^***Core Research for Evolutional Science and Technology (CREST), Tokyo, Japan

Received:

January 25, 2010

Accepted:

May 25, 2010

Published:

September 20, 2010

Keywords:

indoor positioning, particle filter, ZigBee, RSSI, real environment

Abstract

In large indoor commercial spaces constructed recently, services are improved if indoor locations of visitors and employees can be detected. The indoor positioning using ZigBee network based on preobservation of RSSI at positioning areas we propose presents experiments on positioning a mobile ZigBee node on a laboratory floor, including multipath effect. Using our proposal, we determine mobile node location within an accuracy of 3.0 m.

Cite this article as:

J. Tsuji, H. Kawamura, K. Suzuki, T. Ikeda, A. Sashima, and K. Kurumatani, “An Indoor Positioning System Based on Probabilistic Model with ZigBee Sensor Networks,” J. Adv. Comput. Intell. Intell. Inform., Vol.14 No.6, pp. 669-676, 2010.

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References

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This article is published under a Creative Commons Attribution-NoDerivatives 4.0 Internationa License.

[1] [1] J. M. Rabaey, M. J. Ammer, J. L. da Silva, D. Patel, and S. Roundy, “Pico- Radio supports ad hoc ultra-low power wireless networking, Computer,” Vol.33, No.7, pp. 42-48, 2000.

[2] [2] N. Patwari, J. N. Ash, S. Kyperountas, A. O. Hero, R. L. Moses, and N. S. Correal, “Locating the nodes,” IEEE Signal Processing Magazine, Vol.22, No.4, pp. 54-69, 2005.

[3] [3] H. Liu, H. Darabi, P. Banerjee, and J. Liu, “Survey of Wireless Indoor Positioning Techniques and Systems,” IEEE Trans. on Systems, Man, and Cybernetics, Vol.37, No.6, pp. 1067-1080, 2007.

[4] [4] R. Zemek, D. Anzai, S. Hara, K. Yanagihara, and K. Kitayama, “RSSI-based Localization without a Prior Knowledge of Channel Model Parameters,” Int. J. of Wireless Information Networks, Springer Netherlands, Vol.15, No.3-4, pp. 128-136, 2008.

[5] [5] X. Sheng and Y. H. Hu, “Maximum Likelihood Multiple-Source Localization Using Acoustic Energy Measurements with Wireless Sensor Networks,” IEEE Trans. on Signal Processing, Vol.53, No.1, pp.44-54, 2005.

[6] [6] V. Seshadri, G. V. Zaruba, and M. Huber, “A Bayesian Sampling Approach to In-Door Localization of Wireless Devices Using Received Signal Strength Indication,” Proc. of the Third IEEE Int. Conf. on Pervasive Computing and Communications, Vol.2005, pp. 75-84, 2005.

[7] [7] F. Evennou and F.Marx, “Advanced integration of WIFI and inertial navigation systems for indoor mobile positioning,” EURASIP J. on Applied Signal Processing, 2006, pp. 164-174, 2006.

[8] [8] G. V. Zaruba, M. Huber, F. A. Kamangar, and I. Chlamtac, “Indoor location tracking using RSSI readings from a single Wi-Fi access point, Wireless Networks,” Vol.13, No.2, pp. 221-235, 2007.

[9] [9] P. Bahl, and V. Padmanabhan, “RADAR: An In-Building RF-based User Location and Tracking System,” The Proc. of IEEE Infocom, Tel-Aviv, Israel, 2000.

[10] [10] S. K. Yee, “Numerical Solution of Initial Boundary Value of Problems Involving Maxwell’s Equations in Isotropic Media,” IEEE Trans. on Antennas and Propagation, Vol.AP-14, No.3, pp. 302-307, 1966.

[11] [11] A. Taflove, C. S. Hagness, “Computational Electrodynamics: The Finite-Difference Time-Domain Method,” Artech House, Third Edition, 2005.

[12] [12] A. Doucet, N. D. Freitas, and N. Gordon, “Sequential Monte Carlo Methods in Practice,” Springer, 2001.

An Indoor Positioning System Based on Probabilistic Model with ZigBee Sensor Networks

Junpei Tsuji*,***, Hidenori Kawamura*,***, Keiji Suzuki*,***, Takeshi Ikeda**,***, Akio Sashima**,***, and Koichi Kurumatani**,***

Junpei Tsuji^*,***, Hidenori Kawamura^*,***, Keiji Suzuki^,,
Takeshi Ikeda^,, Akio Sashima^,,
and Koichi Kurumatani^,***