Error Bounds and Asymptotic Performance under Mismatch of Multisensor Detection Systems

Abstract

A binary detection problem, when the data are obtained distant sensors, and modelled as stationary Gaussian processes, with different spectra is considered. It is also assumed that inaccurate versions of the true statistical models are utilized, and upper bounds to the probability of error, based on the Chernoff bounding approach are developed. Those bounds also converge to the asymptotic probability of error as the number of data points increased. Conditions for sustaining, in spite of mismatch, exponential convergence of the error probability to zero are also determined. (rh)

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Document Details

Document Type
Technical Report
Publication Date
Jul 01, 1990
Accession Number
ADA228646

Entities

People

  • D. Kazakos

Organizations

  • Syracuse University

Tags

Communities of Interest

  • Materials and Manufacturing Processes
  • Sensors

DTIC Thesaurus Topics

  • Acquisition
  • Command And Control
  • Convergence
  • Data Science
  • Detection
  • Detectors
  • Electrical Engineering
  • Engineering
  • Frequency Diversity
  • Gaussian Processes
  • Information Processing
  • Information Science
  • Multisensors
  • Probability
  • Probability Density Functions
  • Sensor Networks
  • Signal Processing

Fields of Study

  • Mathematics

Readers

  • Calculus or Mathematical Analysis
  • Radio communications and signal processing.
  • Sensor Fusion and Tracking Systems.