Gaussian Interpolation-Based Pedestrian Tracking in Continuous Free Spaces


KIPS Transactions on Computer and Communication Systems, Vol. 19, No. 3, pp. 177-182, Mar. 2012
10.3745/KIPSTB.2012.19.3.177, Full Text:

Abstract

We propose effective motion and observation models for the position of a WiFi-equipped smartphone user in large indoor environments. Three component motion models provide better proposal distribution of the pedestrian`s motion. Our Gaussian interpolation-based observation model can generate likelihoods at locations for which no calibration data is available. These models being incorporated into the particle filter framework, our WiFi fingerprint-based localization algorithm can track the position of a smartphone user accurately in large indoor environments. Experiments carried with an Android smartphone in a multi-story building illustrate the performance of our WiFi localization algorithm.


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Cite this article
[IEEE Style]
I. C. Kim, E. M. Chol and H. K. Oh, "Gaussian Interpolation-Based Pedestrian Tracking in Continuous Free Spaces," KIPS Journal B (2001 ~ 2012) , vol. 19, no. 3, pp. 177-182, 2012. DOI: 10.3745/KIPSTB.2012.19.3.177.

[ACM Style]
In Cheol Kim, Eun Mi Chol, and Hui Kyung Oh. 2012. Gaussian Interpolation-Based Pedestrian Tracking in Continuous Free Spaces. KIPS Journal B (2001 ~ 2012) , 19, 3, (2012), 177-182. DOI: 10.3745/KIPSTB.2012.19.3.177.