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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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
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Abstract	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.
AbstractList	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. 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.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.
Author	Galleani, L.
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SubjectTerms	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
Title	The dynamic Allan variance II: a fast computational algorithm
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