Near-field correlation measurement and evaluation of stationary and cyclostationary stochastic electromagnetic fields

Russer, Johannes A.; Haider, Michael; Baharuddin, Mohd Hafiz; Smartt, Christopher; Wane, Sidina; Baev, Andrey; Kuznetsov, Yu.V.; Thomas, D.W.P.; Russer, P.

doi:10.1109/eumc.2016.7824384

Cited by 9 publications

(4 citation statements)

References 20 publications

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“…For implementing the cyclic averaging of the registered signals in each scanning point the bit rate needs to be known exactly. It can be evaluated for each scanning point separately by estimating the power spectrum of the registered signal revealing the presence of harmonics with frequencies multiple to the fundamental frequency of the periodic deterministic component existing in the registered signal [53], [54].…”

Section: T T T X X H X H Xmentioning

confidence: 99%

Cyclostationary Characterization of Radiated Emissions in Digital Electronic Devices

Kuznetsov

Baev

Konovalyuk

et al. 2020

IEEE Electromagn. Compat. Mag.

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Coupling and Emissions Under Cyclostationary Conditions For convenience, engineers often make the assumption that the statistical behaviour of signals remains constant in time (timeinvariant). However, as the complexity of modern systems increases and the simultaneous presence of several clocked sources of EMI, this assumption is not always valid. Cyclostationary signals have hidden periodicities in the way they transport electromagnetic energy. Cyclostationarity was first studied in connection with mechanical signals. Studying them in connection with EMC is used in identifying patterns of emission from specific areas of PCBs and therefore can assist in taking appropriate remedial actions. The paper by Kuznetsov et al presents an analysis of electrical signals through a process of statistical cyclic averaging to characterize the emission properties for EMC analysis and design. Experimental results are also presented in support of the theoretical analysis. In future issues of the EMC Magazine we will cover topics such as the Electrical Behavior of CFCs, Stochastic EMC Applications, and Lightning Characterization.

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Section: T T T X X H X H Xmentioning

confidence: 99%

Cyclostationary Characterization of Radiated Emissions in Digital Electronic Devices

Kuznetsov

Baev

Konovalyuk

et al. 2020

IEEE Electromagn. Compat. Mag.

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“…Return loss parameters for the manufactured AgNP antennas were measured using an HP 8510B vector network analyzer from Hewlett-Packard (USA). The radiation pattern of the antenna was measured employing an in-house time-domain near-field scanning solution, comprised of a Langer RF-50-1 near-field probe, connected to a LeCroy SDA 813 Zi-A digital oscilloscope [43].…”

Section: Antenna Design and Characterizationmentioning

confidence: 99%

On the sintering of solution-based silver nanoparticle thin-films for sprayed and flexible antennas

et al. 2018

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In this work, we report on the fabrication and characterization of sub-300 nm electrode films based on solution-processed silver nanoparticles (AgNPs). Following the deposition of the electrode material using a scalable and homogenous spray process, the films are treated with thermal or photonic sintering to promote the coalescence of the nanoparticles and in turn decrease the resistivity of the films. After sintering, a resistivity of 63 ± 13 nΩ m is achieved for the AgNP films, which is only by a factor of four larger than the literature value for bulk silver. Both post-deposition treatments show a similar performance with regard to the achieved resistivity. However, photonic sintering avoids the need for thermal annealing at substrate temperatures of 150 °C and above. In addition, the photonic sintering process can easily be embedded in a roll-to-roll process and is extremely fast with light exposure times below 3 ms. Thus, this manufacturing technique paves the way for the use of flexible substrates in electronics. As a simple and practical application, we present the use of AgNP films for antennas operating in the 5 GHz band on flexible polyethylene terephthalate substrate. An original coplanar design is employed for the fabrication of antennas with a single conductive layer that exhibit a maximum return loss and radiation of -27 dB and 95%, respectively.

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“…Modeling of cyclostationary stochastic fields has been addressed in previous studies. [20][21][22] Stochastic EM fields are also considered in literature in the context of fields inside reverberation chambers. 23 Furthermore, variations in the geometry or in material parameters of the structure supporting the wave propagation can be treated with stochastic techniques which use polynomial chaos expansion, stochastic collocation techniques, [24][25][26] or stochastic differential equations.…”

Section: Introductionmentioning

confidence: 99%

“…However, EMI in this case is likely to exhibit cyclostationary rather than stationary properties, ie, mean values of the field and correlation terms will be periodic in time. Modeling of cyclostationary stochastic fields has been addressed in previous studies …”

Section: Introductionmentioning

confidence: 99%

Principal component analysis for efficient characterization of stochastic electromagnetic fields

Haider

Russer

2017

Int J Numerical Modelling

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The propagation of stochastic electromagnetic fields can be accurately modeled using the auto-and cross-correlation spectra of the field components. In this work, we introduce the framework of principal component analysis for reducing the computational cost of handling stochastic electromagnetic fields described by correlation matrices. We consider noisy electromagnetic fields originating from stationary random processes with Gaussian probability distribution. The amount of data obtained by 2-dimensional near-field measurements and by determining the autoand cross-correlation information of electromagnetic interference can become burdensome for further processing even for problems of moderate size. For obtaining the correlation data, 2 measurement probes have to scan a defined grid of measurement points. For each pair of points, the spatial correlations need to be calculated, and hence, the data obtained scales quadratically with the number of sampling points.To reduce the amount of data, we project the given data obtained by measurement or simulation onto directions of maximum variation, the so called principal components, and keep only those principal components which contribute most to the total variance. In this way, the memory demand for storage and further computation of stochastic electromagnetic fields can be reduced significantly. KEYWORDS electromagnetic interference, noisy electromagnetic fields, principal component analysis, stochastic electromagnetic fields Int J Numer Model. 2018;31:e2246.wileyonlinelibrary.com/journal/jnm

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Near-field correlation measurement and evaluation of stationary and cyclostationary stochastic electromagnetic fields

Cited by 9 publications

References 20 publications

Cyclostationary Characterization of Radiated Emissions in Digital Electronic Devices

Cyclostationary Characterization of Radiated Emissions in Digital Electronic Devices

On the sintering of solution-based silver nanoparticle thin-films for sprayed and flexible antennas

Principal component analysis for efficient characterization of stochastic electromagnetic fields

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