A Multi-Variance Analysis in the Time Domain

Abstract

Recently a new technique for characterizing the noise processes affecting oscillators was introduced [1] [2]. This technique minimizes the difference between the estimates of several different variances and their values as predicted by the standard power law model of noise. The method outlined in this paper makes two significant advancements: it uses exclusively time domain variances so that deterministic parameters such as linear frequency drift may be estimated, and it correctly fits the estimates using the chi-square distribution. These changes permit a more accurate fitting at long time intervals where there is the least information. This technique has been applied to both simulated and real data with excellent results.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1992
Accession Number
ADA501917

Entities

People

  • Todd Walter

Organizations

  • Stanford University

Tags

Communities of Interest

  • Energy and Power Technologies
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Analysis Of Variance
  • Confidence Limits
  • Data Science
  • Frequency
  • Frequency Domain
  • Frequency Modulation
  • Information Science
  • Modulation
  • Probability
  • Random Variables
  • Random Walk
  • Standards
  • Statistical Analysis
  • Statistics
  • Stochastic Processes
  • Time Domain
  • Time Intervals

Readers

  • Approximation Theory.
  • Regression Analysis.