A Superresolution Method of ARMA Spectral Estimation,

Abstract

Recently, a method for generating an ARMA spectral estimator model which possessed superresolution performance was developed. This method entailed minimizing a weighted quadratic functional of a set of basic error terms. An issue which remained to be resolved at that time was the selection of the weighting matrix that characterized the functional being minimized. A weighting matrix selection procedure has recently been developed and is reported. The autoregressive parameters are found in this procedure by minimizing a weighted sum of squares of zero mean basic error terms. The new weight selection is chosen to provide more heavy weighting to those terms in the sum which possess lower variances. Empirical evidence indicates that this new weight selections provides superior spectral estimation performance when compared to the original (N-m) to the 4th power weight selection.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1981
Accession Number
ADA099484

Entities

People

  • James A. Cadzow
  • Randolph L. Moses

Organizations

  • Virginia Tech

Tags

Communities of Interest

  • Energy and Power Technologies
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Contracts
  • Data Science
  • Electrical Engineering
  • Estimators
  • Frequency
  • Frequency Domain
  • High Resolution
  • Information Processing
  • Information Science
  • Noise
  • Probability
  • Probability Density Functions
  • Random Variables
  • Signal Processing
  • Statistical Analysis
  • Statistics
  • Virginia

Readers

  • Regression Analysis.
  • Statistical inference.
  • Systems Analysis and Design