Indoor location estimation based on the statistical spatial modeling and radial distributions

Kosuke Okusa, Toshinari Kamakura

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

We study the problem of analyzing indoor location estimation by statistical radial distribution model. In this study, we suppose the observed distance data between transmitter and receiver as a statistical radial distribution. The proposed method is based on the marginal likelihoods of radial distribution generated by positive distribution among the several transmitter radio sites placed in the room. To demonstrate the effectiveness of our method, we conducted two sets of experiments, assessing the accuracy of location estimation of static case and dynamic case. In static experiment, subject is stationary state in some places in the chamber. This experiment is able to measure the precise performance of proposed method. In dynamic experiment, subject is move around in the chamber. This experiment is able to measure the suitability for practical use of proposed method. As a result, our method shows high accuracy for the indoor spatial location estimation compared to other previous methods..

Original languageEnglish
Title of host publicationWCECS 2015 - World Congress on Engineering and Computer Science 2015
PublisherNewswood Limited
Pages835-840
Number of pages6
Volume2220
ISBN (Electronic)9789881404725
Publication statusPublished - 2015
Event2015 World Congress on Engineering and Computer Science, WCECS 2015 - San Francisco, United States
Duration: Oct 21 2015Oct 23 2015

Other

Other2015 World Congress on Engineering and Computer Science, WCECS 2015
CountryUnited States
CitySan Francisco
Period10/21/1510/23/15

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All Science Journal Classification (ASJC) codes

  • Computer Science (miscellaneous)

Cite this

Okusa, K., & Kamakura, T. (2015). Indoor location estimation based on the statistical spatial modeling and radial distributions. In WCECS 2015 - World Congress on Engineering and Computer Science 2015 (Vol. 2220, pp. 835-840). Newswood Limited.