The dynamic Allan variance II: a fast computational algorithm

The stability of an atomic clock can change with time due to several factors, such as temperature, humidity, radiations, aging, and sudden breakdowns. The dynamic Allan variance, or DAVAR, is a representation of the time-varying stability of an atomic clock, and it can be used to monitor the clock b...

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Bibliographic Details
Published in:IEEE transactions on ultrasonics, ferroelectrics, and frequency control Vol. 57; no. 1; pp. 182 - 188
Main Author: Galleani, L.
Format: Journal Article Conference Proceeding
Language:English
Published: New York, NY IEEE 01.01.2010
Institute of Electrical and Electronics Engineers
Subjects:
Aging
Algorithm design and analysis
Algorithms
Atomic clocks
Clocks
Computation
Computer Communication Networks
Computer Simulation
Dynamics
Electric breakdown
Exact sciences and technology
Humidity
Mathematical models
Measurements common to several branches of physics and astronomy
Metrology, measurements and laboratory procedures
Models, Theoretical
Monitoring
Numerical simulation
Physics
Stability
Temperature
Time and frequency
Time Factors
Time series
Time series analysis
Variance
Satellites
Humidity
Time series
Aging
Modelling
Low power
Fast algorithm
Frequency stability
Time-varying systems
Atomic clocks
ISSN:0885-3010, 1525-8955, 1525-8955
Online Access:Get full text
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Summary:The stability of an atomic clock can change with time due to several factors, such as temperature, humidity, radiations, aging, and sudden breakdowns. The dynamic Allan variance, or DAVAR, is a representation of the time-varying stability of an atomic clock, and it can be used to monitor the clock behavior. Unfortunately, the computational time of the DAVAR grows very quickly with the length of the analyzed time series. In this article, we present a fast algorithm for the computation of the DAVAR, and we also extend it to the case of missing data. Numerical simulations show that the fast algorithm dramatically reduces the computational time. The fast algorithm is useful when the analyzed time series is long, or when many clocks must be monitored, or when the computational power is low, as happens onboard satellites and space probes.
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ISSN:0885-3010
1525-8955
1525-8955
DOI:10.1109/TUFFC.2010.1396