Distributed Detection by a Large Team of Sensors in Tandem

Abstract

The problem of decentralized binary hypothesis testing by a team consisting of N decision makers (DMs) in tandem is considered. Each DM receives an observation and transmits a binary message to its successor; the last DM has to decide which hypothesis is true. Necessary and sufficient conditions are derived for the probability of error to asymptotically (as N approaches infinity) go to zero. The result is generalized for multiple hypotheses and multiple messages. An easily implementable suboptimal decision scheme is also considered; necessary and sufficient conditions for the probability of error to asymptotically go to zero are derived for this case as well. The trade off between the complexity of the decision rules and their performance is examined and numerical results are presented.

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Document Details

Document Type
Technical Report
Publication Date
Nov 01, 1989
Accession Number
ADA216607

Entities

People

  • Jason D. Papastavrou
  • Michael Athans

Organizations

  • Massachusetts Institute of Technology

Tags

Communities of Interest

  • C4I
  • Human Systems

DTIC Thesaurus Topics

  • Command And Control
  • Computational Complexity
  • Computer Science
  • Data Fusion
  • Detection
  • Detectors
  • False Alarms
  • Hypotheses
  • Information Theory
  • Measurement
  • Probability
  • Probability Distributions
  • Random Variables
  • Sensor Networks
  • Signal Detection
  • Signal Processing
  • Statistics

Fields of Study

  • Mathematics

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Mathematical Modeling and Probability Theory.
  • Team-Based Human-Centered Cognitive Task Decision Making and Information Performance.