Discrete Periodic Sampling with Jitter and Almost Periodically Correlated Processes

In this paper we consider almost cyclostationary processes with jitter effect. We propose a bootstrap approach based on the Moving Block Bootstrap method to construct pointwise and simultaneous confidence intervals for the Fourier coefficients of the autocovariance function of such processes. In the simulation study we showed how our results can be used to detect the significant frequencies of the autocovariance function. We compared the behavior of our approach for jitter effects caused by perturbations from two distributions, namely uniform and truncated normal. Moreover, we present a real data application of our methodology.

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“…In the following, we use notation introduced in [21]. The process X(t) is not observed continuously but only in instants t k = kh + U k , h > 0.…”

Section: Problem Formulationmentioning

confidence: 99%

Bootstrap for almost cyclostationary processes with jitter effect

Dehay

Dudek

Badaoui

2018

Digital Signal Processing

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“…Jitter variance estimation and compensation methods are discussed. The work [4] studies discrete time observation-based covariance estimation with jitter and delay. It also considers the estimator normality and consistency.…”

Section: Introductionmentioning

confidence: 99%

Co-Prime Sensing with Multiple Periods and Difference Set Analysis in the Presence of Sampling Jitter

Dias¹

2020

Preprint

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Co-prime arrays and samplers with multiple periods is a framework in which the co-prime structure is repeated multiple times. In this paper, the effects of perturbations in sampling locations on the difference set of the prototype co-prime structure with multiple periods is analysed. Based on this analysis, a method to estimate the autocorrelation that maximizes the amount of information extracted from the data is proposed. The advantage is limited only to samplers, and is not observed in antenna arrays. The expression for the number of additional contributors available for estimation is derived. The contributors increase with the increase in the number of periods. In addition, the expressions for the computational complexity are derived in the presence of jitter. This provides an upper bound on the number of multiplications and additions for hardware implementation.

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“…Methods for estimating the jitter variance and for compensating it have also been addressed. Covariance estimation from discrete time observations under jitter and delay conditions is studied in [3], and consistency and asymptotic normality of the estimators are established. System identification under the influence of stochastic sampling jitter noise is considered in [4].…”

Section: Introductionmentioning

confidence: 99%

Co-prime sampling jitter analysis

Dias

Srirangarajan

2017

2017 25th European Signal Processing Conference (EUSIPCO)

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Abstract-Co-prime arrays and samplers are popular subNyquist schemes for estimating second order statistics at the Nyquist rate. This paper focuses on the perturbations in the array locations or sampling times, and analyzes its effect on the difference set. Based on this analysis we propose a method to estimate the autocorrelation which makes best use of the sampled data in order to improve the estimation accuracy of the autocorrelation and hence the spectral estimate. Our analysis indicates that such an advantage is limited only to samplers, and does not carry over to the antenna arrays. In addition, we obtain expressions for the computational complexity of the autocorrelation estimation and provide an upper bound on the number of multiplications and additions required for its hardware implementation.

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Discrete Periodic Sampling with Jitter and Almost Periodically Correlated Processes

Abstract: Continuous time process, Almost periodic covariance, Spectral covariance, Discrete time sampling, Jitter, Consistent estimator, 62G05, 62G20,

Cited by 10 publications

References 9 publications

Bootstrap for almost cyclostationary processes with jitter effect

Bootstrap for almost cyclostationary processes with jitter effect

Co-Prime Sensing with Multiple Periods and Difference Set Analysis in the Presence of Sampling Jitter

Co-prime sampling jitter analysis

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