Fingerprinting Bayesian Algorithm for Indoor Location Determination 


Vol. 35,  No. 6, pp. 888-894, Jun.  2010


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  Abstract

For the indoor positioning, wireless fingerprinting is most favorable because fingerprinting is most accurate among the technique for wireless network based indoor positioning which does not require any special equipments dedicated for positioning. The deployment of a fingerprinting method consists of off-line phase and on-line phase and more efficient and accurate methods have been studied. This paper proposes a bayesian algorithm for wireless fingerprinting and indoor location determination using fuzzy clustering with bayesian learning as a statistical learning theory.

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  Cite this article

[IEEE Style]

J. J. Lee, J. W. Kwon, M. A. Jung, S. R. Lee, "Fingerprinting Bayesian Algorithm for Indoor Location Determination," The Journal of Korean Institute of Communications and Information Sciences, vol. 35, no. 6, pp. 888-894, 2010. DOI: .

[ACM Style]

Jang Jae Lee, Jang Woo Kwon, Min A Jung, and Seong Ro Lee. 2010. Fingerprinting Bayesian Algorithm for Indoor Location Determination. The Journal of Korean Institute of Communications and Information Sciences, 35, 6, (2010), 888-894. DOI: .

[KICS Style]

Jang Jae Lee, Jang Woo Kwon, Min A Jung, Seong Ro Lee, "Fingerprinting Bayesian Algorithm for Indoor Location Determination," The Journal of Korean Institute of Communications and Information Sciences, vol. 35, no. 6, pp. 888-894, 6. 2010.

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pISSN : 1226 - 4717
eISSN : 2287 - 3880