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Uncaught signal imputation for accuracy enhancement of WLAN-based positioning systems

Published:06 November 2012Publication History

ABSTRACT

In this paper we propose a technique to enhance the accuracy of WiFi fingerprint-based localization by imputing uncaught access point (AP) signals of WiFi fingerprints. Two techniques were developed for this; one is to impute uncaught AP signals by referring to WiFi radio map (WRM) fingerprints at the very previous location, another is referring to WRM fingerprints obtained by predicting the next location. When we measured the accuracy of localization at an E-Mart, Seoul, Korea and a KAIST Library, Daejeon, Korea with and without uncaught signal imputation, the imputed signal resulted in around 30% better accuracy improvement than the signals without imputation. In addition, the imputation methods using WRM information showed significantly better accuracy than using a fixed value for uncaught AP signals. This indicates that the uncaught signal imputation, which was overlooked in the WLAN-based localization, should be incorporated with other filtering techniques for a more reliable and accurate localization.

References

  1. Y. Chen, Q. Yang, J. Yin, and X. Chai. Power-efficient access-point selection for indoor location estimation. IEEE Transactions on Knowledge and Data Engineering, 18(7):877--888, july 2006. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Kalman, Rudolph, and Emil. A New Approach to Linear Filtering and Prediction Problems. Transactions of the ASME--Journal of Basic Engineering, 82(Series D):35--45, 1960.Google ScholarGoogle Scholar
  3. M. Lee and D. Han. Voronoi tessellation based interpolation method for wi-fi radio map construction. IEEE Communications Letters, 16(3):404--407, 2012.Google ScholarGoogle ScholarCross RefCross Ref
  4. R. Ouyang, A. Wong, and K. Woo. Indoor localization via discriminatively regularized least square classification. International Journal of Wireless Information Networks, 18:57--72, 2011. 10.1007/s10776-011-0133-5.Google ScholarGoogle ScholarCross RefCross Ref
  5. A. Thiagarajan, L. Ravindranath, K. LaCurts, S. Madden, H. Balakrishnan, S. Toledo, and J. Eriksson. Vtrack: accurate, energy-aware road traffic delay estimation using mobile phones. In Proceedings of the 7th ACM Conference on Embedded Networked Sensor Systems, SenSys '09, pages 85--98, New York, NY, USA, 2009. ACM. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. F. Vanheel, J. Verhaevert, E. Laermans, I. Moerman, and P. Demeester. Automated linear regression tools improve rssi wsn localization in multipath indoor environment. EURASIP J. Wireless Comm. and Networking, 2011:38, 2011.Google ScholarGoogle ScholarCross RefCross Ref
  7. G. Welch and G. Bishop. An introduction to the kalman filter. Technical report, Chapel Hill, NC, USA, 1995. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. Z.-l. Wu, C.-h. Li, J. K.-Y. Ng, and K. R. P. H. Leung. Location estimation via support vector regression. IEEE Transactions on Mobile Computing, 6(3):311--321, Mar. 2007. Google ScholarGoogle ScholarDigital LibraryDigital Library

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  1. Uncaught signal imputation for accuracy enhancement of WLAN-based positioning systems

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          • Published in

            cover image ACM Conferences
            MobiGIS '12: Proceedings of the First ACM SIGSPATIAL International Workshop on Mobile Geographic Information Systems
            November 2012
            112 pages
            ISBN:9781450316996
            DOI:10.1145/2442810
            • Conference Chair:
            • Chi-Yin Chow

            Copyright © 2012 ACM

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            Association for Computing Machinery

            New York, NY, United States

            Publication History

            • Published: 6 November 2012

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