Joint PDF Construction for Sensor Fusion and Distributed Detection

Abstract

A novel method of constructing a joint probability density function (PDF) under H(sub 1), when the joint PDF under H(sub 0) is known, is developed. It has direct application in distributed detection systems. The construction is based on the exponential family, and it is shown that asymptotically the constructed PDF is optimal. The generalized likelihood ratio test (GLRT) is derived based on this method for the partially observed linear model. Interestingly, the test statistic is equivalent to the clairvoyant GLRT, which uses the true PDF under H(sub 1), even if the noise is nonGaussian.

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Document Details

Document Type
Technical Report
Publication Date
Jul 01, 2010
Accession Number
ADA564774

Entities

People

  • Darren Emge
  • Quan Ding
  • Steven Kay

Organizations

  • University of Rhode Island

Tags

Communities of Interest

  • Biomedical
  • C4I
  • Sensors

DTIC Thesaurus Topics

  • Air Force
  • Air Force Research Laboratories
  • Biomedical Engineering
  • Construction
  • Data Fusion
  • Detection
  • Detectors
  • False Alarms
  • Gaussian Noise
  • Information Science
  • Measurement
  • Military Research
  • Noise
  • Probability
  • Sensor Fusion
  • Simulations

Fields of Study

  • Engineering

Readers

  • Neurological Diseases/Conditions/Disorders
  • Statistical inference.