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A Multi-Classifier Approach for WiFi-Based Positioning System

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Electrical Engineering and Applied Computing

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 90))

Abstract

WLAN fingerprint-based positioning systems are a viable solution for estimating the location of mobile stations. Recently, various machine learning techniques have been applied to the WLAN fingerprint-based positioning systems to further enhance their accuracy. Due to the noisy characteristics of RF signals as well as the lack of the study on environmental factors affecting the signal propagation, however, the accuracy of the previously suggested systems seems to have a strong dependence on numerous environmental conditions. In this work, we have developed a multi-classifier for the WLAN fingerprint-based positioning systems employing a combining rule. According to the experiments of the multi-classifier performed in various environments, the combination of the multiple numbers of classifiers could significantly mitigate the environment-dependent characteristics of the classifiers. The performance of the multi-classifier was found to be superior to that of the other single classifiers in all test environments; the average error distances and their standard deviations were much more improved by the multi-classifier in all test environments.

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Acknowledgments

This research was supported by the MKE(The Ministry of Knowledge Economy), Korea, under the ITRC(Information Technology Research Center) support program supervised by the NIPA(National IT Industry Promotion Agency) (NIPA-2010-(C1090-1011-0013)), and by the National Research Foundation of Korea(NRF) grant funded by the Korea government(MEST) (No. 2008-0061123).

Author information

Authors and Affiliations

  1. Department of Information and Communications Engineering, Korea Advanced Institute of Science and Technology, 373-1 Kusong-Dong, Yuseong-gu, Daejeon, 305-701, Korea

    Jikang Shin & Suk Hoon Jung

  2. Department of Electrical Engineering, Korea Advanced Institute of Science and Technology, 373-1 Kusong-Dong, Yuseong-gu, Daejeon, 305-701, Korea

    Giwan Yoon

  3. Department of Computer Science, Korea Advanced Institute of Science and Technology, 373-1 Kusong-Dong, Yuseong-gu, Daejeon, 305-701, Korea

    Dongsoo Han

Authors
  1. Jikang Shin
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  2. Suk Hoon Jung
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  3. Giwan Yoon
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  4. Dongsoo Han
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Corresponding author

Correspondence to Jikang Shin .

Editor information

Editors and Affiliations

  1. The University of Hong Kong, Hung To Road, Hong Kong, 3739, China, People's Republic

    Sio-Iong Ao

  2. School of Engineering, Applied Mathematics and Computing, Cranfield University, Cranfield, MK43 0AL, Montserrat

    Len Gelman

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Shin, J., Jung, S.H., Yoon, G., Han, D. (2011). A Multi-Classifier Approach for WiFi-Based Positioning System. In: Ao, SI., Gelman, L. (eds) Electrical Engineering and Applied Computing. Lecture Notes in Electrical Engineering, vol 90. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-1192-1_12

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  • DOI: https://doi.org/10.1007/978-94-007-1192-1_12

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  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-94-007-1191-4

  • Online ISBN: 978-94-007-1192-1

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