Time and Frequency (Time-Domain) Characterization, Estimation, and Prediction of Precision Clocks and Oscillators

Allan, David W.

doi:10.1109/t-uffc.1987.26997

Cited by 688 publications

(353 citation statements)

References 13 publications

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“…If a GNSS receiver is driven by a stable oscillator whose accumulated time error due to random frequency fluctuations (RMS x ( P )) [Allan, 1987] is smaller than the receiver's observation noise (typically 3 mm for the ionosphere-free carrier phase linear combination), the temporal variations of the receiver clock offset can be constrained over intervals p (typically 1 min to 1 h), e.g., by a linear or quadratic polynomial (cf. Weinbach and Schön [2011] or Weinbach [2013]).…”

Section: Receiver Clock Modelingmentioning

confidence: 99%

Improved GPS‐based coseismic displacement monitoring using high‐precision oscillators

Weinbach

Schön

2015

Geophysical Research Letters

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The determination of high‐frequency displacements using Global Navigation Satellite Systems (GNSS) observations with sampling frequencies > 1 Hz has attracted much interest in recent years, e.g., in seismology. We propose a new concept for GPS Precise Point Positioning (PPP) that takes advantage of a highly stable oscillator connected to the GPS receiver by modeling its behavior. We show that the high‐frequency noise of kinematic GPS height estimates can be reduced by a factor of up to 4 to the level of 2–3 mm and the overall standard deviation including systematic long periodic errors by a factor of up to 2 to the 1 cm level. Consequently, valuable small and currently hidden vertical displacements can be detected that are not visible with classical PPP. Using data of the 2010 Chile earthquake, we demonstrate that coseismic vertical displacements with an amplitude of only 5 mm can be recovered using PPP with the proposed clock modeling strategy.

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Section: Receiver Clock Modelingmentioning

confidence: 99%

Improved GPS‐based coseismic displacement monitoring using high‐precision oscillators

Weinbach

Schön

2015

Geophysical Research Letters

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“…For example, it has been used for over 30 years as a standard routine measure of frequency stability in lasers (see Fukuda, Tachikawa, and Kinoshita (2003)) or atomic clocks (see Allan (1987)). More recently, the WV has also been used with optical sensors (see Kebabian, Herndon, and Freedman (2005)), various types of gas monitoring spectrometers (see Bowling, Sargent, Tanner, and Ehleringer (2003); Werle, Mücke, and Slemr (1993)), sonic anemometer-thermometers (see Loescher, Ocheltree, Tanner, Swiatek, Dano, Wong, Zimmerman, Campbell, Stock, Jacobsen et al (2005)), inertial sensors (see Guerrier (2009);El-Sheimy, Hou, and Niu (2008)), radio-astronomical instrumentation (see Schieder and Kramer (2001)).…”

Section: Robust Estimation Of the Wavelet Variancementioning

confidence: 99%

Estimation of Time Series Models via Robust Wavelet Variance

Guerrier

Molinari

Victoria‐Feser

2014

AJS

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A robust approach to the estimation of time series models is proposed. Taking from a new estimation method called the Generalized Method of Wavelet Moments (GMWM) which is an indirect method based on the Wavelet Variance (WV), we replace the classical estimator of the WV with a recently proposed robust M-estimator to obtain a robust version of the GMWM. The simulation results show that the proposed approach can be considered as a valid robust approach to the estimation of time series and state-space models.

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“…Since drift will also occur due to changes in saline temperature, this must be carefully controlled. We measure drift using the Allan Variance (Allan 1987), AV 2 v (τ ), which characterizes the stability of systems as a function of the averaging time τ . The Allan deviation AV v (τ ) is the square root of the Allan variance.…”

Section: Performance Parametersmentioning

confidence: 99%

“…Data are divided into bins based on an averaging time τ and averaged in each bin (i), yielding an averagev i . The Allan Variance (AV 2 v (τ )) can be written as a function of the averaging time τ (Allan 1987):…”

Section: Performance Parametersmentioning

confidence: 99%

Evaluation of EIT system performance

et al. 2011

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Abstract. An electrical impedance tomography (EIT) system images internal conductivity from surface electrical stimulation and measurement. Such systems necessarily comprise multiple design choices from cables and hardware design to calibration and image reconstruction. In order to compare between EIT systems and to study the consequences of changes in system performance, this paper describes a systematic approach to evaluate the performance of the EIT systems. The system to be tested is connected to a saline phantom in which calibrated contrasting test objects are systematically positioned using a position controller. A set of evaluation parameters are proposed which characterize: i) data and image noise, ii) data accuracy, iii) detectability of single contrasts and distinguishability of multiple contrasts, and iv) accuracy of reconstructed image (amplitude, resolution, position and ringing). Using this approach, we evaluate three different EIT systems and illustrate the use of these tools to evaluate and compare performance. In order to facilitate use of this approach, all details of the phantom, test objects and position controller design are made publicly available including the source code of the evaluation and reporting software.

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Time and Frequency (Time-Domain) Characterization, Estimation, and Prediction of Precision Clocks and Oscillators

Cited by 688 publications

References 13 publications

Improved GPS‐based coseismic displacement monitoring using high‐precision oscillators

Improved GPS‐based coseismic displacement monitoring using high‐precision oscillators

Estimation of Time Series Models via Robust Wavelet Variance

Evaluation of EIT system performance

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