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An adaptive oscillator noise analysis using factor analysis

机译:使用因子分析的自适应振荡器噪声分析

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摘要

Multivariance oscillator noise analysis methods provide precise measurements of some noise sources of a high-performance oscillator, while others are inaccurate due to poor observability and an ill-conditioned problem. The ill-conditioned problem can be solved by separating the averaging time manually. The disadvantage of this strategy is that difficulties in execution arise when measuring noise sources from dynamic variances. This paper introduce an adaptive noise intensive coefficients estimator which separates the averaging time automatically and thus is executable on dynamic variances. Two cost functions, one of deterministic linear frequency drift and the other of noise intensity coefficients, are introduced to form the estimator. The estimator is tested with simulated data. In addition, a dynamic total variance is computed from more than 8.2 years of GPS clock data, and 31765 groups of noise intensity coefficients are estimated using the adaptive estimator. The results show that the adaptive noise intensity coefficient estimator is as precise as the multivariance oscillator noise analysis methods and is robust.
机译:多方差振荡器噪声分析方法可对高性能振荡器的某些噪声源进行精确测量,而另一些则由于可观察性差和病态问题而不准确。病态问题可以通过手动分离平均时间来解决。该策略的缺点是,在测量来自动态方差的噪声源时,执行困难。本文介绍了一种自适应噪声密集型系数估计器,它可以自动分离平均时间,因此可以在动态方差上执行。引入两个成本函数,一个是确定性线性频率漂移,另一个是噪声强度系数,以形成估计器。估算器使用模拟数据进行测试。另外,从超过8.2年的GPS时钟数据中计算出动态总方差,并使用自适应估计器估计了31765组噪声强度系数。结果表明,自适应噪声强度系数估计器与多方差振荡器噪声分析方法一样精确,并且具有鲁棒性。

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