Gaussian Interpolation-Based Pedestrian Tracking in Continuous Free Spaces 


Vol. 19,  No. 3, pp. 177-182, Jun.  2012
10.3745/KIPSTB.2012.19.3.177


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  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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[IEEE Style]

I. C. Kim, E. M. Chol, H. K. Oh, "Gaussian Interpolation-Based Pedestrian Tracking in Continuous Free Spaces," The KIPS Transactions:PartB , 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. The KIPS Transactions:PartB , 19, 3, (2012), 177-182. DOI: 10.3745/KIPSTB.2012.19.3.177.

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