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A Distributed Message Passing Algorithm for Sensor Localization

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Artificial Neural Networks – ICANN 2007 (ICANN 2007)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4668))

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Abstract

We propose a fully distributed message passing algorithm based on expectation propagation for the purpose of sensor localization. Sensors perform noisy measurements of their mutual distances and their relative angles. These measurements form the basis for an iterative, local (i.e. distributed) algorithm to compute the sensor’s locations including uncertainties for these estimates. This approach offers a distributed, computationally efficient and flexible framework for information fusion in sensor networks.

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References

  1. Ihler, A.T., Fisher III, J.W., Moses, R.L., Willsky, A.S.: Nonparametric belief propagation for self-calibration in sensor networks. In: Information Processing in Sensor Networks (2004)

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  3. Moses, R.L., Krishnamurthy, D., Patterson, R.: A self-localization method for wireless sensor networks. EURASIP Journal on Applied Signal Processing 4, 348–358 (2003)

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  5. Priyantha, N.B., Balakrishnan, H., Demaine, E., Teller, S.: Anchor-free distributed localization in sensor networks.Technical Report TR-892, MIT LCS (April 2003)

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Author information

Authors and Affiliations

  1. Bren School of Information and Computer Science, UC Irvine, CA 92697-3425, USA

    Max Welling & Joseph J. Lim

Authors
  1. Max Welling
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  2. Joseph J. Lim
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Editor information

Joaquim Marques de Sá Luís A. Alexandre Włodzisław Duch Danilo Mandic

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© 2007 Springer-Verlag Berlin Heidelberg

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Welling, M., Lim, J.J. (2007). A Distributed Message Passing Algorithm for Sensor Localization. In: de Sá, J.M., Alexandre, L.A., Duch, W., Mandic, D. (eds) Artificial Neural Networks – ICANN 2007. ICANN 2007. Lecture Notes in Computer Science, vol 4668. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74690-4_78

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  • DOI: https://doi.org/10.1007/978-3-540-74690-4_78

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-74689-8

  • Online ISBN: 978-3-540-74690-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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