Optimum Local Decision Space Partitioning for Distributed Detection

Chung Chieh Lee, J. J. Chao

Research output: Contribution to journalArticlepeer-review

73 Scopus citations


We consider a distributed detection system which consists of a number of independent local detectors and a fusion center. The decision statistics and performance characteristics (i.e., the false alarm probabilities and detection probabilities) of the local detectors are assumed given. Communication is assumed only between each local detector and the fusion center and is one-way from the former to the latter. The fusion center receives decisions from the local detectors and combines them for a global decision. Instead of a one-bit hard decision, we propose that each local detector provides the fusion center with multiple-bit decision which represents its decision and, conceptually, its degree of confidence on that decision. Generating a multiple-bit local decision entails a subpartitioning of the local decision space, whose optimization is studied. We show that the proposed system significantly outperforms the one in which each local detector provides only a hard decision. We also show that, based on optimum subpartitioning of local decision space, the detection performance increases monotonically with the number of partitions.

Original languageEnglish (US)
Pages (from-to)536-544
Number of pages9
JournalIEEE Transactions on Aerospace and Electronic Systems
Issue number4
StatePublished - Jan 1 1989

ASJC Scopus subject areas

  • Aerospace Engineering
  • Electrical and Electronic Engineering
  • Computer Networks and Communications


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