24. Polynomial-Based Methods for Localization in Multiagent Systems

  1. Seyed A. (Reza) Zekavat4 and
  2. R. Michael Buehrer5
  1. Iman Shames1,
  2. Barış Fidan2,
  3. Brian D. O. Anderson1 and
  4. Hatem Hmam3

Published Online: 6 SEP 2011

DOI: 10.1002/9781118104750.ch24

Handbook of Position Location: Theory, Practice, and Advances

Handbook of Position Location: Theory, Practice, and Advances

How to Cite

Shames, I., Fidan, B., Anderson, B. D. O. and Hmam, H. (2011) Polynomial-Based Methods for Localization in Multiagent Systems, in Handbook of Position Location: Theory, Practice, and Advances (eds S. A. (. Zekavat and R. M. Buehrer), John Wiley & Sons, Inc., Hoboken, NJ, USA. doi: 10.1002/9781118104750.ch24

Editor Information

  1. 4

    Michigan Technological University, Houghton, MI, USA

  2. 5

    Virginia Tech, Blacksburg, VA, USA

Author Information

  1. 1

    The Australian National University and National ICT Australia, Canberra, Australia

  2. 2

    University of Waterloo, Waterloo, Canada

  3. 3

    Defence Science & Technology Organisation, Edinburgh, Australia

Publication History

  1. Published Online: 6 SEP 2011
  2. Published Print: 16 SEP 2011

ISBN Information

Print ISBN: 9780470943427

Online ISBN: 9781118104750

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Keywords:

  • multiagent systems;
  • noisy target localization;
  • polynomial function optimization;
  • semidefinite programming (SDP);
  • sensor network localization;
  • sum of squares (SOS) approach

Summary

This chapter reviews a series of results obtained in the field of localization that are based on polynomial optimization. First, it provides a review of a set of polynomial function optimization tools, including sum of squares (SOS). Then the chapter presents several applications of these tools in various sensor network localization tasks. As the first application, it proposes a method based on SOS relaxation for node localization using noisy measurements and describes the solution through semidefinite programming (SDP). Later, the chapter applies this method to address the problems of target localization in the presence of noise and relative reference frame determination based on range and bearing measurements. Finally, it provides some simulation and experiment results to show the applicability of the methods.

Controlled Vocabulary Terms

mathematical programming; multi-agent systems; noise measurement; polynomials; wireless sensor networks