Reduction of All-Pole Parameter Estimator Bias by Successive Autocorrelation.

Abstract

Conventional all-pole parameter estimators applied to noise corrupted all-pole sequences result in biased estimates. This paper describes a procedure by which reduction of this bias is accomplished by applying pole-preserving, signal to noise ratio improving functions to the sequences. Correlation like pole-preserving functions are investigated and pole dependent signal to noise ratio improvement is described. An all-pole parameter estimator using successive application of a pole-preserving function (successive autocorrelation) is given. Comparison is made with the least squares combination of the higher order Yule-Walker equations, an approach to bias reduction reported by Cadzow. Successive autocorrelation is found to result in improved performance, with estimates of higher Q poles being most effectively enhanced. (Author)

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1982
Accession Number
ADA124830

Entities

People

  • Darcy Mcginn
  • Don H. Johnson

Organizations

  • Rice University

Tags

DTIC Thesaurus Topics

  • Algorithms
  • Autocorrelation
  • Computations
  • Covariance
  • Difference Equations
  • Electrical Engineering
  • Engineering
  • Equations
  • Estimators
  • Frequency
  • Gaussian Noise
  • Ions
  • Military Research
  • New York
  • Noise
  • Sequences
  • Signal Processing

Readers

  • Approximation Theory.