Performance Parameters for Quasi Canonical Class A Non-Gaussian Noise; Source Distribution Law mu = 0, Propagation Law gamma = 2

Abstract

Non-Gaussian noise is very frequently the dominant background interference in a wide variety of communication situations, where in some general sense it is desired to transmit information from one point in space and time to another. Recently, Class A noise is distinguished by its coherent, transientless passage through the linear front end stages of typical receivers. Examples in applications arise in both active systems: (1) in sonar, in radar, in acoustical and electromagnetic (EM) telecommunications; (2) as a result of natural and man-made phenomena, e.g., lightning, ocean ambient noise, and biological mechanisms, automobile ignitions, electrical tools, and arctic ice noise. This report presents extensive numerical results for Class A noise; these consist of (1) probability densities; (2) cumulative probability distributions; (3) and in particular, various special statistics associated with Class A noise, which are needed in the evaluation of general receiver performance, i.e., for optimum weak-signal detection and estimation, and for threshold performance comparisons generally. A concise description of all these quantities is included in the text. In addition, various methods of carrying out the numerical evaluations are described in detail. Several alternative forms for the characteristic function of the normalized instantaneous amplitude have been derived, in terms of incomplete Gamma functions, and are suitable for large or small arguments.

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Document Details

Document Type
Technical Report
Publication Date
Jun 15, 1986
Accession Number
ADA175958

Entities

People

  • Albert H. Nuttall
  • David Middleton
  • Ira B. Cohen

Organizations

  • Naval Underwater Systems Center

Tags

Communities of Interest

  • C4I
  • Energy and Power Technologies
  • Materials and Manufacturing Processes
  • Space

DTIC Thesaurus Topics

  • Accuracy
  • Additives (Chemicals)
  • Communication Systems
  • Detection
  • Detectors
  • Distribution Functions
  • Gaussian Noise
  • Noise
  • Operating Systems
  • Probability
  • Probability Density Functions
  • Probability Distributions
  • Random Variables
  • Security
  • Signal Processing
  • Statistics
  • Warning Systems

Readers

  • Oceanography.
  • Radio communications and signal processing.
  • Statistical inference.

Technology Areas

  • Space