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A study of the allan variance for constant-mean nonstationary processes

Authors
Guerrier, Stephane
Molinari, Roberto
Zhang, Yuming
Published in IEEE Signal Processing Letters. 2017, vol. 24, no. 8, p. 1257-1260
Abstract The Allan Variance (AV) is a widely used quantity in areas focusing on error measurement as well as in the general analysis of variance for autocorrelated processes in domains such as engineering and, more specifically, metrology. The form of this quantity is widely used to detect noise patterns and indications of stability within signals. However, the properties of this quantity are not known for commonly occurring processes whose covariance structure is non-stationary and, in these cases, an erroneous interpretation of the AV could lead to misleading conclusions. This paper generalizes the theoretical form of the AV to some non-stationary processes while at the same time being valid also for weakly stationary processes. Some simulation examples show how this new form can help to understand the processes for which the AV is able to distinguish these from the stationary cases and hence allow for a better interpretation of this quantity in applied cases.
Keywords MetrologySensor CalibrationBias-InstabilityLongitudinal StudiesHaar Wavelet VarianceHeteroscedasticity
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XU, Haotian et al. A study of the allan variance for constant-mean nonstationary processes. In: IEEE Signal Processing Letters, 2017, vol. 24, n° 8, p. 1257-1260. https://archive-ouverte.unige.ch/unige:96032

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Deposited on : 2017-08-07

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