Stochastic EMI sources localization based on time domain near-field data

Gorbunova, Anastasia; Konovalyuk, Maxim; Baev, Andrey; Kuznetsov, Yu.V.

doi:10.1109/ursigass.2014.6929548

Cited by 4 publications

(7 citation statements)

References 8 publications

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“…Using (29) to eliminateH x andH y in (28), this yields the propagator (19). Similar surface impedance conditions can be derived mutatis mutandis for the other fields components.…”

Section: Appendixmentioning

confidence: 76%

“…The latter may be a wire array, for example, driven by voltages radiating partially correlated field components [14]. The knowledge of the ACF within planar surfaces at different distances from the source can be useful to assist source reconstruction methods [28], [29], [30], [31], far-field estimation [32], [33], as well as recently introduced phase-resolved scanning [34] and Emission Source Microscopy (ESM) methods [35]. Furthermore, the method can be used in conjunction with Huygens box method -also in its incomplete version when the radiation is suppressed through some box faces [33] -to augment the information on random field fluctuations.…”

Section: Introductionmentioning

confidence: 99%

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Wigner-Function-Based Propagation of Stochastic Field Emissions From Planar Electromagnetic Sources

Gradoni

Arnaut

Creagh

et al. 2018

IEEE Trans. Electromagn. Compat.

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A note on versions:The version presented here may differ from the published version or from the version of record. If you wish to cite this item you are advised to consult the publisher's version. Please see the repository url above for details on accessing the published version and note that access may require a subscription. Abstract-Modelling the electromagnetic radiation from modern digital systems -acting effectively as extended, stochastic sources as part of a complex architecture -is a challenging task. We follow an approach here based on measuring and propagating field-field autocorrelation functions (ACFs) after suitable averaging. From the modelling side, we use the Wigner transform of the ACFs to describe random wave fields in terms of position and direction of propagation variables. An approximate propagator for the components of the radiated magnetic field is constructed for these ACFs based on a linear flow map. Field-field ACFs at aperture level are obtained from scanning measurements of complex sources. Distance and spatial resolution of the scanning plane is less than a wavelength from the source plane to capture the imprint of evanescent waves in the nearfield ACFs. Near-field scanning and efficient near-to-far field propagation is carried out and compared with measurements. Results of this study will be useful to assist far-field predictions, source reconstruction, and emission source microscopy.

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“…Using (29) to eliminateH x andH y in (28), this yields the propagator (19). Similar surface impedance conditions can be derived mutatis mutandis for the other fields components.…”

Section: Appendixmentioning

confidence: 76%

Section: Introductionmentioning

confidence: 99%

Wigner-Function-Based Propagation of Stochastic Field Emissions From Planar Electromagnetic Sources

Gradoni

Arnaut

Creagh

et al. 2018

IEEE Trans. Electromagn. Compat.

View full text Add to dashboard Cite

show abstract

“…For the standard PC normalization a T · a = I, the variables v m lie on an N -dimensional hypersphere. 9 Since N i=1 ρ 2 m i = 1, the projection v m therefore lies on or within a 2-D circle of unit correlations for any pair of PCs. The nearer v m lies to this circle, i.e., the smaller the residual loading 1 − (a 2 m i + a 2 m j ), the more dominant the PCs i and 9 For the alternative normalizations a T · a = λ 2 or λ −2 , the v m lie on an N -dimensional hyperellipsoid with semi-axes λ i or 1/λ i , respectively.…”

Section: G Geometric Representation Of Pc Loadings and Scoresmentioning

confidence: 98%

“…Closed-form "analytical-stochastic" characterization [12] typically relies on assumed idealized space-time homogeneity of sources and fields (stationarity in its wide or strict sense), in order to enable estimating ensemble averages of the field from sample spectral or temporal averages (ergodicity) and to characterize correlation by a single function [9]- [11]. Externally generating an ensemble of random excitation signals is usually impossible in circuits, while generating an ensemble of different circuit layouts defies the purpose of evaluating a chosen PCB design.…”

Section: Numerical-stochastic Characterization Of Inhomogeneous Ramentioning

confidence: 99%

Empirical Emission Eigenmodes of Printed Circuit Boards

Arnaut

Obiekezie

Thomas

2014

IEEE Trans. Electromagn. Compat.

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It is shown that radiated emissions from circuits can be efficiently decomposed and represented using principal component analysis (PCA). A hierarchical set of orthonormal spatial eigenmodes and their associated amplitudes are extracted from data for an emitted field that is scanned and measured across a planar area and wide frequency band. This decomposition is applied to the magnetic tangential field intensity for emissions from an analog transmission-line based circuit. The inhomogeneity of the autocorrelation matrix driving the PCA algorithm is experimentally demonstrated. Eigenmodes, loadings, and scores of the principal components are calculated and interpreted physically. Across the selected frequency band, PCA achieves efficiency savings of one to two orders or magnitude for the representation of emitted radiation.Index Terms-Diagnostics, magnetic field probe, orthogonal expansion, principal component analysis (PCA), radiated emissions.

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“…Stochastic electromagnetic fields with Gaussian probability distribution can be described completely by the autocorrelation spectrum of each field variable and the cross-correlation spectra of field variables at distinct points of observation [13]- [19]. Characterization of a stochastic electromagnetic field requires the sampling of the EM field in pairs of observation points and the determination of the cross-correlation functions for all pairs of field samples.…”

Section: Introductionmentioning

confidence: 99%

Modeling of Noisy EM Field Propagation Using Correlation Information

Russer

2015

IEEE Trans. Microwave Theory Techn.

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In this paper, an efficient method for the numerical simulation of near-and far-field propagation of stochastic electromagnetic (EM) fields is presented. The method is based on the transformation of field correlation dyadics using Green's functions or the field transfer functions computed for deterministic fields. The method accounts for arbitrary correlations between the noise radiation sources and allows to compute the spatial distribution of the spectral energy density of noisy electromagnetic sources. The introduced methodology can be combined with available electromagnetic modeling tools. It is shown that the method of moments can be applied to solve noisy electromagnetic field problems by network methods applying correlation matrix techniques. Examples demonstrating the strong influence of the correlation between the sources on the spatial distribution of the radiated noise field are presented.Index Terms-Electromagnetic interference, near-field scanning, noisy electromagnetic fields, stochastic electromagnetic fields. 0018-9480

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Stochastic EMI sources localization based on time domain near-field data

Cited by 4 publications

References 8 publications

Wigner-Function-Based Propagation of Stochastic Field Emissions From Planar Electromagnetic Sources

Wigner-Function-Based Propagation of Stochastic Field Emissions From Planar Electromagnetic Sources

Empirical Emission Eigenmodes of Printed Circuit Boards

Modeling of Noisy EM Field Propagation Using Correlation Information

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