Sensor fusion enhancement via optimized stochastic resonance at local sensors

Bin Liu, Satish Iyengar, Hao Chen, James H. Michels, Pramod Kumar Varshney

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

2 Scopus citations

Abstract

This paper considers the decentralized fusion problem involving local sensor detection as well as the fusion of decisions transmitted over non-ideal transmission channels in a wireless sensor network. Prime emphasis is given to the enhancement of several fusion rules using a recently developed stochastic resonance methodology applied at the local sensors. Further, it is shown that the optimal form of the stochastic resonance probability mass density for the decentralized sensor fusion problem retains the same form as that previously developed for the single sensor case.

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

Other

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

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Keywords

  • Decentralized detection
  • Rayleigh fading channels
  • Sensor fusion
  • Stochastic resonance

ASJC Scopus subject areas

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

Cite this

Liu, B., Iyengar, S., Chen, H., Michels, J. H., & Varshney, P. K. (2007). Sensor fusion enhancement via optimized stochastic resonance at local sensors. In FUSION 2007 - 2007 10th International Conference on Information Fusion [4408142] https://doi.org/10.1109/ICIF.2007.4408142