A Comparison of the Burg and the Known-Autocorrelation Autoregressive Spectral Analysis of Complex Sinusoidal Signals in Additive White Noise,

Abstract

Burg's algorithm for Maximum Entropy autoregressive spectral estimation is analyzed for the cases of one and two complex sinusoidal signals in additive white noise. For the latter case are found two biases which can account for the line splitting and line shifting that occur in simulation studies when the SNR is very high. These biases vanish completely if the two complex sinusoids are in phase quadrature at the middle of the data record; if there is an integral number of half-cycles of difference frequency contained in the data record, then the power level of the spectral estimate will be biased although the effects believed to cause splitting and shifting will be eliminated. Results of simulation studies to support these conjectures are presented. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1979
Accession Number
ADA080020

Entities

People

  • R. W. Herring

Organizations

  • Communications Research Centre Canada

Tags

DTIC Thesaurus Topics

  • Additives (Chemicals)
  • Algorithms
  • Autocorrelation
  • Data Science
  • Data Sets
  • Difference Frequency
  • Frequency
  • Information Science
  • Noise
  • Power
  • Power Spectra
  • Simulations
  • Sine Waves
  • Spectra
  • Statistical Distributions
  • Statistics
  • White Noise

Fields of Study

  • Engineering

Readers

  • Control Systems Engineering.
  • Spectroscopy.
  • Statistical inference.