skip to main content
10.1145/1641804.1641874acmconferencesArticle/Chapter ViewAbstractPublication PagesmswimConference Proceedingsconference-collections
research-article

The role of colinearity of sensors in target localization using distance measurements

Published:26 October 2009Publication History

ABSTRACT

We consider estimating the location of a target moving in a 2D plane by combining distance measurements from multiple sensors. Given that available energy in sensors is at a premium, it must be conserved by selecting fewer number of sensors to measure distance and communicate to a central tracker. While elsewhere we have presented various heuristics which together can form the basis for selection of a minimum of three sensors, in this paper we provide a theoretical basis for the heuristic that suggests that the three sensors must not be colinear.

References

  1. J. Aslam, Z. Butler, V. Crepi, G. Cybenko, and D. Rus. Tracking a moving object with a binary sensor network. In ACM SenSys, 2003. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. P. Bahl and V.N. Padmanabhan. RADAR: An in-building RF-based user location and tracking system. In IEEE INFOCOM, 2000.Google ScholarGoogle ScholarCross RefCross Ref
  3. Y. Chen, J.A. Francisco, W. Trappe, and R.P. Martin. A practical approach to landmark deployment for indoor localization. In SECON 2006, 2006.Google ScholarGoogle ScholarCross RefCross Ref
  4. V. Isler and R. Bajcsy. The Sensor Selection Problem for bounded uncertainty Sensing Models. In IPSN 2005, 2005. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. J. Liu, J. Reich, and F. Zhao. Collaborative in-network processing for target tracking. In EURASIP JASP, vol. 4, no. 378--391, 2003. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. V.P. Sadaphal. Tracking target using energy constrained sensor networks. In Ph.D. dissertation, Dept. of CSE, IIT Delhi, India., 2007.Google ScholarGoogle Scholar
  7. V.P. Sadaphal and B.N. Jain. Sensor Selection Heuristics for Tracking Sensor Networks. In HiPC 2005, LNCS, Springer Verlag., 2005. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. V.P. Sadaphal and B.N. Jain. Random and Periodic sleep schedules for target detection in sensor networks. In MASS 2007, Pisa, Italy., 2007.Google ScholarGoogle ScholarCross RefCross Ref
  9. V.P. Sadaphal and B.N. Jain. Tracking target using sensor networks: target detection and route activation under energy constraints. In COMSWARE 2008, Bangalore, India, 2008.Google ScholarGoogle ScholarCross RefCross Ref
  10. T. He, C. Huang, B.M. Blum, J.A. Stankovic, and T. Abdelzaher. Range-Free Localization Schemes for Large Scale Sensor Networks. In Proc. of MobiCom, 2003. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. H. Wang, K. Yao, and D. Estrin. Information-theoretic approaches for sensor selection and placement in sensor networks for target localization and tracking. In J. of Comm. and Networks, Vol. 7, No.4, December 2005.Google ScholarGoogle ScholarCross RefCross Ref
  12. H. Wang, K. Yao, G. Pottie, and D. Estrin. Entropy-based sensor selection heuristic for target localization. In IPSN 2004, Proceedings of The Third International Symposium on Information Processing in Sensor Networks. ACM Press, 2004. Google ScholarGoogle ScholarDigital LibraryDigital Library

Index Terms

  1. The role of colinearity of sensors in target localization using distance measurements

    Recommendations

    Comments

    Login options

    Check if you have access through your login credentials or your institution to get full access on this article.

    Sign in
    • Published in

      cover image ACM Conferences
      MSWiM '09: Proceedings of the 12th ACM international conference on Modeling, analysis and simulation of wireless and mobile systems
      October 2009
      438 pages
      ISBN:9781605586168
      DOI:10.1145/1641804

      Copyright © 2009 ACM

      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

      Publisher

      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 26 October 2009

      Permissions

      Request permissions about this article.

      Request Permissions

      Check for updates

      Qualifiers

      • research-article

      Acceptance Rates

      Overall Acceptance Rate398of1,577submissions,25%

    PDF Format

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader