Fractional Difference Prewhitening in Atomic Clock Modeling

Abstract

A new approach to atomic clock classification has been enabled by the application of long-memory, or fractionally integrated, noise constructs. While the spectral properties of the long-memory noises are consistent with the historical 1.f(alpha) approach, they also allow a range of estimation strategies, in both spectral and time domains, for the classification of atomic clock behavior. These fractionally integrated noises are analyzed and applied to atomic timescales in this research, with particular emphasis on a prewhitening technique using fractional differencing which allows the separation of clock noise autocorrelation from clock rate and drift. Results from simulation studies show the utility of the fractional differencing approach both for simple fractionally integrated processes, and more complex processes which are more characteristic of atomic clock noise.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2003
Accession Number
ADA485536

Entities

People

  • C. Ekstrom
  • L. Breakiron
  • L. Schmidt

Organizations

  • United States Naval Observatory

Tags

DTIC Thesaurus Topics

  • Additives (Chemicals)
  • Atomic Clocks
  • Autocorrelation
  • Clocks
  • Confidence Limits
  • Data Science
  • Data Sets
  • Frequency
  • Frequency Domain
  • Gaussian Processes
  • Information Science
  • Noise
  • Normal Distribution
  • Random Variables
  • Statistical Processes
  • Time Intervals
  • White Noise

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