GPS-Based Time Error Estimates Provided by Smoothing, Wiener, and Kalman Filters: A Comparative Study

Abstract

GPS timing plays a critical role in modern practice of time errors estimate and synchronization. Big noise of the GPS-based measured data and inherent non-stationary of a time error cause major difficulties here. In spite of theoretical separation of the application fields for the filters (stationary and non-stationary signals), GPS-based time error processes require more explicit practical answer. Indeed, what process may be practically treated as a stationary one and, to opposite, how to recognize a non-stationary case? In this report we answer these questions by numerically and show that for the same transient time the following filter should be used to get the best accuracy for the known initial fractional frequency offset y(sub 0) (time error rate) of oscillator, namely an average smoother for |y(sub o)| < r(sub 1), the Wiener filter for r(sub 1) less than or equal to |y(sub 0)| less than or equal to r(sub 2), and the Kalman filter for r(sub 2) < |y(sub 0)|, where r(sub 1) and r(sub 2) are coordinates dependent on the required accuracy. We prove this conclusion by the example of a time error estimate of the rubidium standard based on the reference tinting signals of the Motorola GPS UT+ Oncore Timing receiver.

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Document Details

Document Type
Technical Report
Publication Date
Nov 01, 2000
Accession Number
ADA485688

Entities

People

  • 0. Ibarra-mamano
  • A. V. Marienko
  • M. Torres-cisneros
  • Y. S. Shmaliy

Organizations

  • Universidad de Guanajuato

Tags

Communities of Interest

  • Materials and Manufacturing Processes
  • Space

DTIC Thesaurus Topics

  • Algorithms
  • Clocks
  • Estimators
  • Filters
  • Filtration
  • Frequency
  • Kalman Filters
  • Local Oscillators
  • Mathematical Models
  • Measurement
  • Models
  • Noise
  • Oscillators
  • Stationary Processes
  • Statistical Algorithms
  • Time Intervals
  • White Noise

Fields of Study

  • Engineering

Readers

  • Approximation Theory.
  • Positioning, Navigation, and Timing (PNT) Technology.
  • Statistical inference.

Technology Areas

  • Space