Fusion of threshold rules for target detection in wireless sensor networks

Mengxia Zhu, Song Ding, Qishi Wu, R. R. Brooks, N. S.V. Rao, S. S. Iyengar

Research output: Contribution to journalArticlepeer-review

49 Scopus citations


We propose a binary decision fusion rule that reaches a global decision on the presence of a target by integrating local decisions made by multiple sensors. Without requiring a priori probability of target presence, the fusion threshold bounds derived using Chebyshev's inequality ensure a higher hit rate and lower false alarm rate compared to the weighted averages of individual sensors. The Monte Carlo-based simulation results show that the proposed approach significantly improves target detection performance, and can also be used to guide the actual threshold selection in practical sensor network implementation under certain error rate constraints.

Original languageEnglish (US)
Article number18
JournalACM Transactions on Sensor Networks
Issue number2
StatePublished - Feb 1 2010
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications


  • Binary decision fusion
  • Chebyshev inequality
  • False alarm rate
  • Hit rate
  • ROC curve
  • Wireless sensor network


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