Statistics of Narrowband White Noise Derived from Clipped Broadband White Noise

Abstract

Broadband white Gaussian noise is modelled as a series of sine and cosine functions of discrete frequencies up to a maximum frequency. The series coefficients are Gaussian with uniform variance across the frequency band. For a given sample, the Nyquist-spaced values are generated for a full period of the lowest frequency sinusoid and a peak factor is imposed, clipping the values. The resulting signal is discrete-Fourier transformed via the fast Fourier transform, hard filtered at a prescribed bandwidth, and then inverse transformed to give a set of values for the narrow band signal sample, and these values are used to update a histogram. When a sufficient number of signal samples are generated, the resulting distribution is fitted to a Gaussian distribution by a least-squares technique. It is found that the resulting distributions are noticeably non-Gaussian down to a bandwidth ratio of 1:4, below which the distribution appears to be Gaussian with a reduced variance depending on the peak factor. For a bandwidth ratio of 1:40, it is found that peak factors as low as 1.7 or even 1.5 have little effect on the narrowband distribution.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Feb 01, 1992
Accession Number
ADA248597

Entities

People

  • W. M. Wynn

Tags

Communities of Interest

  • Energy and Power Technologies
  • Weapons Technologies

DTIC Thesaurus Topics

  • Bandwidth
  • Broadband
  • Coefficients
  • Discrete Fourier Transforms
  • Fast Fourier Transforms
  • Filters
  • Frequency
  • Frequency Bands
  • Gaussian Distributions
  • Gaussian Noise
  • Histograms
  • Mountains
  • Narrowband
  • Navy
  • Rocky Mountains
  • Statistics
  • White Noise

Readers

  • Mathematics or Statistics
  • Radar Systems Engineering.
  • Statistical inference.

Technology Areas

  • Space