Decentralized Detection by a Large Number of Sensors,

Abstract

Consider the decentralized detection problem, in which a number N of identical sensors transmit a finite valued function of their observations to a fusion center which the decides which one of M alternative hypotheses is true. Consider the case where the number of sensors tends to infinity. Then show that it is asymptotically optimal to divide the sensors into M(M-1)/2 groups, with all sensors in each group using the same decision rule in deciding what to transmit. Show also how the optimal number of sensors in each group may be determined by solving a mathematical programming problem. For the special case of two hypotheses and binary messages the solution simplifies considerably: it is optimal (asymptotically, as N approaches infinity) to have each sensor perform an identical likelihood ratio test and the optimal threshold is very easy to determine numerically.

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Document Details

Document Type
Technical Report
Publication Date
Apr 01, 1987
Accession Number
ADA180327

Entities

People

  • John N. Tsitsiklis

Organizations

  • Massachusetts Institute of Technology

Tags

Communities of Interest

  • Human Systems

DTIC Thesaurus Topics

  • Computer Programming
  • Damage Detection
  • Detection
  • Detectors
  • Equations
  • Hypotheses
  • Inequalities
  • Linear Programming
  • Mathematical Programming
  • Military Research
  • Notation
  • Observation
  • Optimization
  • Probability
  • Probability Distributions
  • Random Variables
  • Statistics

Fields of Study

  • Mathematics

Readers

  • Computer Networking
  • Sensor Fusion and Tracking Systems.
  • Statistical inference.