Predicting Long-Term Frequency Stability: Stochastic Oscillator Noise Analysis

Cheng, Weiwei; Nie, Guigen; Wang, Pingli; Zhang, Caihong; Gao, Yuping

doi:10.1109/tuffc.2019.2898109

Cited by 5 publications

(5 citation statements)

References 17 publications

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“…This is because: To test the modified stochastic ONA method, a strong presentation of deterministic frequency drift should be seen. In the real data test of [ 7 ], frequency drift does not have significant influence on the behaviors of some onboard rubidium frequency standards within 168 days. Such data cannot test the capability of stochastic ONA in predicting drift contaminated stabilities.…”

Section: Resultsmentioning

confidence: 99%

“…Since the likelihood (or conditional probability) of:

is zero, we estimate a

confidence region of

instead. This extension is realized by using convex optimization techniques ( Appendix A.2 ), and we call it stochastic ONA [ 7 ].…”

Section: Stochastic Onamentioning

confidence: 99%

“…Recently, Thêo- [ 5 ] and parabolic variances [ 6 ] were also proposed. The authors proposed an oscillator noise analysis method called stochastic ONA [ 7 ]. The method predicts long-term frequency stabilities using convex optimization techniques.…”

Section: Introductionmentioning

confidence: 99%

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Predicting Long-Term Stability of Precise Oscillators under Influence of Frequency Drift

Cheng

Nie

2018

Sensors

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High-performance oscillators, atomic clocks for instance, are important in modern industries, finance and scientific research. In this paper, the authors study the estimation and prediction of long-term stability based on convex optimization techniques and compressive sensing. To take frequency drift into account, its influence on Allan and modified Allan variances is formulated. Meanwhile, expressions for the expectation and variance of discrete-time Hadamard variance are derived. Methods that reduce the computational complexity of these expressions are also introduced. Tests against GPS precise clock data show that the method can correctly predict one-week frequency stability from 14-day measured data.

show abstract

Section: Resultsmentioning

confidence: 99%

“…Since the likelihood (or conditional probability) of:

is zero, we estimate a

confidence region of

instead. This extension is realized by using convex optimization techniques ( Appendix A.2 ), and we call it stochastic ONA [ 7 ].…”

Section: Stochastic Onamentioning

confidence: 99%

See 1 more Smart Citation

Predicting Long-Term Stability of Precise Oscillators under Influence of Frequency Drift

Cheng

Nie

2018

Sensors

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“…To evaluate periodic variations from frequency stability estimates of GNSS satellite AFS, we modify the stochastic model proposed in [28]:…”

Section: Characterizing Periodic Variations Using Frequency Stability...mentioning

confidence: 99%

“…respectively. Details about the optimization models, Equations ( 6) and ( 9), and their numerical solutions can be found in references [28,29].…”

Section: Characterizing Periodic Variations Using Frequency Stability...mentioning

confidence: 99%

Characterizing Periodic Variations of Atomic Frequency Standards via Their Frequency Stability Estimates

Cheng

Nie

Zhu

2023

Sensors

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The onboard atomic frequency standard (AFS) is a crucial element of Global Navigation Satellite System (GNSS) satellites. However, it is widely accepted that periodic variations can influence the onboard AFS. The presence of non-stationary random processes in AFS signals can lead to inaccurate separation of the periodic and stochastic components of satellite AFS clock data when using least squares and Fourier transform methods. In this paper, we characterize the periodic variations of AFS using Allan and Hadamard variances and demonstrate that the Allan and Hadamard variances of the periodics are independent of the variances of the stochastic component. The proposed model is tested against simulated and real clock data, revealing that our approach provides more precise characterization of periodic variations compared to the least squares method. Additionally, we observe that overfitting periodic variations can improve the precision of GPS clock bias prediction, as indicated by a comparison of fitting and prediction errors of satellite clock bias.

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Ultra-low lattice thermal conductivity and enhanced thermoelectric performance in Ag2−xSe1/3S1/3Te1/3 via anion permutation and cation modulation

et al. 2021

Journal of Alloys and Compounds

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Predicting Long-Term Frequency Stability: Stochastic Oscillator Noise Analysis

Cited by 5 publications

References 17 publications

Predicting Long-Term Stability of Precise Oscillators under Influence of Frequency Drift

Predicting Long-Term Stability of Precise Oscillators under Influence of Frequency Drift

Characterizing Periodic Variations of Atomic Frequency Standards via Their Frequency Stability Estimates

Ultra-low lattice thermal conductivity and enhanced thermoelectric performance in Ag2−xSe1/3S1/3Te1/3 via anion permutation and cation modulation

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