Channel aware target localization in wireless sensor networks

Onur Ozdemir, Ruixin Niu, Pramod K. Varshney

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

In this paper, we propose a new maximum-likelihood (ML) target location estimator which uses quantized sensor data and wireless channel statistics in a wireless sensor network. The novelty of our approach comes from the fact that imperfect channel statistics between wireless sensors and the fusion center are incorporated in the localization algorithm. We call this approach "channel-aware target localization". Furthermore, we derive the Cramer-Rao lower bound as a performance bound for our channel-aware ML estimator. Simulation results are presented to show that the performance of the channel-aware ML location estimator is quite close to its theoretical performance bound even with relatively small number of sensors and it has superior performance compared to that of the channel-unaware ML estimator.

Original languageEnglish (US)
Title of host publicationFUSION 2007 - 2007 10th International Conference on Information Fusion
DOIs
StatePublished - Dec 1 2007
EventFUSION 2007 - 2007 10th International Conference on Information Fusion - Quebec, QC, Canada
Duration: Jul 9 2007Jul 12 2007

Publication series

NameFUSION 2007 - 2007 10th International Conference on Information Fusion

Other

OtherFUSION 2007 - 2007 10th International Conference on Information Fusion
CountryCanada
CityQuebec, QC
Period7/9/077/12/07

Keywords

  • Cramer-Rao lower bound
  • Imperfect communication channels
  • Target localization
  • Wireless sensor networks

ASJC Scopus subject areas

  • Hardware and Architecture
  • Information Systems
  • Signal Processing
  • Software

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  • Cite this

    Ozdemir, O., Niu, R., & Varshney, P. K. (2007). Channel aware target localization in wireless sensor networks. In FUSION 2007 - 2007 10th International Conference on Information Fusion [4408075] (FUSION 2007 - 2007 10th International Conference on Information Fusion). https://doi.org/10.1109/ICIF.2007.4408075