DETECTION OF NON-GAUSSIAN PROCESSES IN NON GAUSSIAN NOISE

Abstract

The detection of stochastic processes in noise is considered, under the assumption that neither the signal nor the noise need be Gaussian. The detector structure is found in terms of the semiinvariants of the signal and noise processes. The general detector structure is extremely complicated, but a threshold form may be obtained. For symmetric processes with zero mean and independent sampling, the energy detector is obtained. Error probabilities are computed for the energy detector with non-Gaussian signal process and/or non Gaussian noise. It is shown that large degradations in sensitivity occur if the noise is highly impulsive in character, but the non-Gaussian character of the signal process is found to have very little effect on the detector sensitivity.

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 1963
Accession Number
AD0408986

Entities

People

  • Frank C. Ogg

Organizations

  • Johns Hopkins University

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Air Force
  • Background Noise
  • Communication Systems
  • Detection
  • Detectors
  • Digital Data
  • Electronic Warfare
  • Gaussian Distributions
  • Gaussian Noise
  • Gaussian Processes
  • Government Procurement
  • Governments
  • Order Statistics
  • Power Series
  • Probability
  • Statistics
  • United States

Readers

  • Acoustics.
  • Statistical inference.