Advertisement

A Study of Indoor Positioning Algorithm to Secure WLAN RSSI Reliability

  • Jinhyung Park
  • Sunghun Kang
  • Wonhyuk Lee
  • Seunghae Kim
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 181)

Abstract

This study has obtained the results of practical positioning using IEEE802.11-based WLAN which makes it possible to get access to a mobile network anytime and anywhere as it becomes more common in public buildings, colleges and airports and has been used in diverse sectors thanks to mobility, portability and convenience and analyzed indoor positioning methods. Based on the results of the indoor and outdoor positioning experiments, the characteristics of WLAN signals in indoor environment were analyzed. In addition, this study has examined a plan to secure RSSI reliability and indoor positioning algorithm which enhances accuracy in a candidate group for measurement of positioning spots. Then, this study has attempted to figure out the applicability of WLAN positioning system in indoor environment through an experiment.

Keywords

Positioning RSSI Reliability WLAN 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Malekpour, A., Ling, T.C., Lim, W.C.: Location Determination Using Radio Frequency RSSI and Deterministic Algorithm. In: IEEE CNSRC (2008)Google Scholar
  2. 2.
    Hoene, C., Willmann, J.: Four-way TOA and Software-Based Trilateration of IEEE 802.11 Devices. In: IEEE PIMRC (2008)Google Scholar
  3. 3.
    Gwon, Y., Jain, R., Kawahara, T.: Robust Indoor Location Estimation of Stationary and Mobile Users. In: IEEE Infocom (2004)Google Scholar
  4. 4.
    Nafarieh, A., Ilow, J.: A Testbed for Localizing Wireless LAN Devices Using Received Signal Strength. In: IEEE CNSRC (2008)Google Scholar
  5. 5.
    Kang, S.: A Study of intelligent in-door positioning algorithm based on IEEE 802.11 signal strength, Master’s Thesis in School of Electronical Engineering & Computer Science, Kyungpook National University (2009)Google Scholar
  6. 6.
    Youssef, M., Agrawala, A., Shankar, A.U.: WLAN Location Determination via Clustering and Probability Distributions. In: IEEE PerCom (2002)Google Scholar
  7. 7.
    Luo, R.C.: Mobile user localization in wireless sensor network using grey prediction method. In: IEEE IECON (2005)Google Scholar
  8. 8.
    Choi, T.Y.: A Study on in-door positioning methaod using RSSI value in IEEE 802.15.4 WPAN, Master’s Thesis in School of Electronical Engineering & Computer Science, Kyungpook National University (2007)Google Scholar
  9. 9.
    Lim, C.B., Kang, S.H., Cho, H.H., Park, S.W., Park, J.G.: An Enhanced Indoor Localization Algorithm Based on IEEE 802.11 WLAN Using RSSI and Multiple Parameters. In: IEEE ICSNC, p. 238 (2010)Google Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2012

Authors and Affiliations

  • Jinhyung Park
    • 1
  • Sunghun Kang
    • 2
  • Wonhyuk Lee
    • 1
  • Seunghae Kim
    • 1
  1. 1.Korea Institute of Science and Technology InformationDaejeonKorea
  2. 2.Kyungpook National UniversityDaeguKorea

Personalised recommendations