Distributed decision fusion using the Neyman-Pearson criterion

Ji Wang, Moshe Kam

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

3 Scopus citations

Abstract

Performance of a parallel binary decision fusion architecture is considered where both the local detectors and the Decision Fusion Center use the Neyman-Pearson criterion. The architecture comprises N local detectors in parallel, each sending a binary decision to a fusion center for integration. The algorithm designed here fixes the global false alarm rate and attempts to compute the local detector thresholds and the global fusion rule that achieve the maximum global detection probability. The key computational requirement is to find the roots of a certain Nth order polynomial. We compare the performance of our method with the performance of the Person-by-Person Optimization (PBPO) approach and that of a centralized detection scheme.

Original languageEnglish (US)
Title of host publicationFUSION 2014 - 17th International Conference on Information Fusion
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9788490123553
StatePublished - Jan 1 2014
Externally publishedYes
Event17th International Conference on Information Fusion, FUSION 2014 - Salamanca, Spain
Duration: Jul 7 2014Jul 10 2014

Other

Other17th International Conference on Information Fusion, FUSION 2014
CountrySpain
CitySalamanca
Period7/7/147/10/14

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All Science Journal Classification (ASJC) codes

  • Information Systems

Cite this

Wang, J., & Kam, M. (2014). Distributed decision fusion using the Neyman-Pearson criterion. In FUSION 2014 - 17th International Conference on Information Fusion [6916075] Institute of Electrical and Electronics Engineers Inc..