Adaptive decision fusion for distributed passive detection system

Ran Tao*, Tian Wang, Juan Zhao

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

For decision fusion in a distributed passive detection system, the probabilities of detection of each receiver may be unknown or vary with time. An on-line adaptive decision fusion algorithm is presented. The algorithm is based on Neyman-Pearson criterion. The algorithm uses local decisions to estimate the unknown probabilities of the detection of each receiver to implement an optimal decision fusion. Computer simulation results demonstrate its feasibility and effectiveness.

Original languageEnglish
Pages (from-to)265-267
Number of pages3
JournalBeijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology
Volume25
Issue number3
Publication statusPublished - Mar 2005

Keywords

  • Adaptive algorithm
  • Distributed detection
  • Neyman-Pearson criterion
  • Optimal decision fusion

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