Decentralized sequential detection with sensors performing sequential tests

Research output: Contribution to journalArticlepeer-review

Abstract

A decentralized sequential detection problem is considered where a set of sensors making independent observations must decide which of the given two hypotheses is true. Decision errors are penalized through a common cost function, and each time step taken by the sensors as a team is assigned a positive cost. It is shown that optimal sensor decision functions can be found in the class of generalized sequential probability ratio tests (GSPRTs) with monotonically convergent thresholds. A technique is presented for obtaining the optimal thresholds. The performance of the optimal policy is compared with that of a policy which uses SPRTs at each of the sensors.

Original languageEnglish (US)
Pages (from-to)292-305
Number of pages14
JournalMathematics of Control, Signals, and Systems
Volume7
Issue number4
DOIs
StatePublished - Dec 1 1994

Keywords

  • Decentralized detection
  • Distributed decision making
  • Dynamic programming
  • Optimal stopping rules
  • Sequential analysis
  • Stochastic teams

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Signal Processing
  • Control and Optimization
  • Applied Mathematics

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