Skip to main content

The Analysis of Anchor Placement for Self-localization Algorithm in Wireless Sensor Networks

  • Conference paper
Advances in Wireless Sensor Networks (CWSN 2012)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 334))

Included in the following conference series:

Abstract

In range-based localization systems of wireless sensor networks, a small fraction of nodes in the network have known locations while the remaining keep unknown. However, with the change of the anchors distribution, the positioning accuracy of the localization algorithm is quite different. Therefore, we use parameter estimation theory to analyze the node location problem, model the distance measuring with multiplicative normal noise model, and drive the Cramer-Rao lower bound of location. Through simulation we find an effective anchor placement strategy. Compared with random deployment, the proposed strategy provides higher positioning accuracy.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • 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.

References

  1. Wang, F., Shi, L., Ren, F.: Self-Localization Systems and Algorithms for Wireless Sensor Networks. Journal of Software 16(5), 857–868 (2005)

    Article  Google Scholar 

  2. Girod, L., Bychovskiy, V., Elson, J., Estrin, D.: Locating tiny sensors in time and space: A case study. In: Werner, B. (ed.) Proc. of the 2002 IEEE Int’l Conf. on Computer Design: VLSI in Computers and Processors, pp. 214–219. IEEE Computer Society, Freiburg (2002)

    Chapter  Google Scholar 

  3. Harter, A., Hopper, A., Steggles, P., Ward, A., Webster, P.: The anatomy of a context-aware application. In: Proc. of the 5th Annual ACM/IEEE Int’l Conf. on Mobile Computing and Networking, pp. 59–68. ACM Press, Seattle (1999)

    Chapter  Google Scholar 

  4. Girod, L., Estrin, D.: Robust range estimation using acoustic and multimodal sensing. In: Proc. of the IEEE/RSJ Int’l Conf. on Intelligent Robots and Systems, IROS 2001, vol. 3, pp. 1312–1320. IEEE Robotics and Automation Society, Maui (2001)

    Google Scholar 

  5. Niculescu, D., Nath, B.: Ad hoc positioning system (APS) using AoA. In: Proc. of the IEEE INFOCOM 2003, vol. 3, pp. 1734–1743. IEEE Computer and Communications Societies, San Francisco (2003)

    Google Scholar 

  6. Niculescu, D., Nath, B.: DV based positioning in ad hoc networks. Journal of Telecommunication Systems 22(1/4), 267–280 (2003)

    Article  Google Scholar 

  7. Doherty, L., Pister, K.S.J., Ghaoui, L.E.: Convex position estimation in wireless sensor networks. In: Proc. of the IEEE INFOCOM 2001, vol. 3, pp. 1655–1663. IEEE Computer and Communications Societies, Anchorage (2001)

    Google Scholar 

  8. Shang, Y., Ruml, W., Zhang, Y., et al.: Localization from mere connectivity in sensor networks. In: Proc. of the 4th ACM Int’l Symp. on Mobile Ad Hoc Networking & Computing, pp. 201–212. ACM Press, New York (2003)

    Google Scholar 

  9. Shang, Y., Ruml, W., Zhang, Y.: Localization from connectivity in sensor networks. IEEE Trans. on Parallel and Distributed Systems 15(11), 961–973 (2004)

    Article  Google Scholar 

  10. Patwari, N., Hero, A., Perkins, M., Correal, N., O’Dea, R.: Relative location estimation in wireless sensor networks. IEEE Trans. Signal Process. 51(8), 2137–2148 (2003)

    Article  Google Scholar 

  11. Catovic, A., Sahinoglu, Z.: The Cramer-Rao bounds of hybrid TOA/RSS and TDOA/RSS location estimation schemes. IEEE Communications Letters 8(10), 626–628 (2004)

    Article  Google Scholar 

  12. Latsoudas, G., Sidiropoulos, N.D.: A fast and Effective Multidimensional Scaling Approach for Node Localization in Wireless Sensor Networks. IEEE Trans. Signal Process. 55(10), 5121–5127 (2007)

    Article  MathSciNet  Google Scholar 

  13. Shi, H.C., Li, X.L., Shang, Y.: Cramer-Rao Bound Analysis of Quantized RSSI Based Localization in WSN. In: Proc. of the 2005 11th International Conference on Parallel and Distributed Systems, ICPADS 2005. IEEE (2005)

    Google Scholar 

  14. Li, X.L., Shi, H.C., Shang, Y.: Selective anchor placement algorithm for ad-hoc wireless sensor networks. In: Proc. of IEEE Int. Conf. Communications, ICC 2008, pp. 2359–2363 (2008)

    Google Scholar 

  15. Savvides, A., Garber, W., Adlakha, S., Moses, R., Srivastava, M.B.: On the Error Characteristics of Multihop Node Localization in Ad-Hoc Sensor Networks. In: Zhao, F., Guibas, L.J. (eds.) IPSN 2003. LNCS, vol. 2634, pp. 317–332. Springer, Heidelberg (2003)

    Chapter  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

Huang, L., Wang, F., Ma, C., Duan, W. (2013). The Analysis of Anchor Placement for Self-localization Algorithm in Wireless Sensor Networks. In: Wang, R., Xiao, F. (eds) Advances in Wireless Sensor Networks. CWSN 2012. Communications in Computer and Information Science, vol 334. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-36252-1_12

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-36252-1_12

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-36251-4

  • Online ISBN: 978-3-642-36252-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics