[go: up one dir, main page]
More Web Proxy on the site http://driver.im/
Skip to main content

Particle Swarm Optimization for Auto-localization of Nodes in Wireless Sensor Networks

  • Conference paper
Adaptive and Natural Computing Algorithms (ICANNGA 2013)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7824))

Included in the following conference series:

Abstract

In this paper, we consider the problem of auto-localization of the nodes of a static Wireless Sensor Network (WSN) where nodes communicate through Ultra Wide Band (UWB) signaling. In particular, we investigate auto-localization of the nodes assuming to know the position of a few initial nodes, denoted as “beacons”. In the considered scenario, we compare the location accuracy obtained with the widely used Two-Stage Maximum-Likelihood algorithm with that achieved with an algorithm based on Particle Swarming Optimization (PSO). Accurate simulation results show that the latter can significantly outperform the former.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Subscribe and save

Springer+ Basic
£29.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
GBP 19.95
Price includes VAT (United Kingdom)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
GBP 35.99
Price includes VAT (United Kingdom)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
GBP 44.99
Price includes VAT (United Kingdom)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

References

  1. Gezici, S., Poor, H.V.: Position estimation via ultra-wide- band signals. Proc. IEEE 97(2), 386–403 (2009)

    Article  Google Scholar 

  2. Zhang, J., Orlik, P.V., Sahinoglu, Z., Molisch, A.F., Kinney, P.: UWB systems for wireless sensor networks. Proc. IEEE 97(2), 313–331 (2009)

    Article  Google Scholar 

  3. Wade, H.F.: Position-location solutions by Taylor-series estimation. IEEE Trans. Aerosp. Electron. Syst. AES-12(2), 187–194 (1976)

    Article  Google Scholar 

  4. Mensing, C., Plass, S.: Positioning algorithms for cellular networks using TDOA. In: Proceedings of the 2006 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2006, vol. 4 (May 2006)

    Google Scholar 

  5. Shen, G., Zetik, R., Thomä, R.S.: Performance comparison of TOA and TDOA based location estimation algorithms in LOS environment. In: Proceedings of the 5th Workshop on Positioning, Navigation and Communication, WPNC 2008 (2008)

    Google Scholar 

  6. Schmidt, R.O.: A new approach to geometry of range difference location. IEEE Trans. Aerosp. Electron. Syst. AES-8(6), 821–835 (1972)

    Article  Google Scholar 

  7. Chan, Y., Ho, K.C.: A simple and efficient estimator for hyperbolic location. IEEE Trans. Signal Process 42(8), 1905–1915 (1994)

    Article  MathSciNet  Google Scholar 

  8. Ho, K.C., Xu, W.: An accurate algebraic solution for moving source location using TDOA and FDOA measurements. IEEE Trans. Signal Process. 52(9), 2453–2463 (2004)

    Article  MathSciNet  Google Scholar 

  9. Ho, K.C., Lu, X., Kovavisaruch, L.: Source localization using TDOA and FDOA measurements in the presence of receiver location errors: analysis and solution. IEEE Trans. Signal Process. 55(2), 684–696 (2007)

    Article  MathSciNet  Google Scholar 

  10. Busanelli, S., Ferrari, G.: Improved ultra wideband-based tracking of twin-receiver automated guided vehicles. Journal of Integrated Computer-Aided Engineering 19(1), 3–22 (2012)

    Google Scholar 

  11. Molisch, A.F., Cassioli, D., Chong, C.-C., Emami, S., Fort, A., Kannan, B., Karedal, J., Kunisch, J., Schantz, H.G., Siwiak, K., Win, M.Z.: A comprehensive standardized model for ultrawideband propagation channels. IEEE Trans. Antennas Propagat. 54(11), 3151–3166 (2006)

    Article  Google Scholar 

  12. Dardari, D., Chong, C.C., Win, M.Z.: Threshold-based time-of-arrival estimators in uwb dense multipath channels. IEEE Trans. Commun. 56(8), 1366–1378 (2008)

    Article  Google Scholar 

  13. Kennedy, J., Eberhart, R.: Particle swarm optimization. In: Proc. IEEE International Conf. on Neural Networks, Perth, Australia, IEEE Service Center, Piscataway (1995)

    Google Scholar 

  14. Poli, R., Kennedy, J., Blackwell, T.: Particle swarm optimization. Swarm Intelligence Journal 1(1) (2007)

    Google Scholar 

  15. Eberhart, R., Kermedy, J.: A new optimizer using particles swarm theory. In: Proc. Sixth International Symposium on Micro Machine and Hmm Science, Nagoya, Japan, IEEE Service Center, Piscataway (1995)

    Google Scholar 

  16. Shi, Y., Eberhart, R.: A modied particle swarm optimizer. In: Proc. IEEE International Conference on Evolutionary Computation, Piscataway, NJ, pp. 69–73 (1999)

    Google Scholar 

  17. Monica, S., Ferrari, G.: Impact of the number of beacons in PSO-based auto-localization in UWB networks. To appear in Proceedings of EvoApplications (2013)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Monica, S., Ferrari, G. (2013). Particle Swarm Optimization for Auto-localization of Nodes in Wireless Sensor Networks. In: Tomassini, M., Antonioni, A., Daolio, F., Buesser, P. (eds) Adaptive and Natural Computing Algorithms. ICANNGA 2013. Lecture Notes in Computer Science, vol 7824. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37213-1_47

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-37213-1_47

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-37212-4

  • Online ISBN: 978-3-642-37213-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics