Treffer: IEEE P2718 Working Group Activity: Open Source Code Development for the Characterization of Unintentional Stochastic Radiators

Title:
IEEE P2718 Working Group Activity: Open Source Code Development for the Characterization of Unintentional Stochastic Radiators
Contributors:
Colella, Emanuel, Russer, Johanne, Baharuddin, Mohd Hafiz, Russer, Peter, Haider, Michael, Thomas, David W. P., Gradoni, Gabriele, Bastianelli, Luca, Moglie, Franco, Primiani, Valter Mariani
Publication Year:
2024
Collection:
Università Politecnica delle Marche: IRIS
Document Type:
Fachzeitschrift article in journal/newspaper
File Description:
ELETTRONICO
Language:
English
Relation:
volume:13; issue:1; firstpage:43; lastpage:50; numberofpages:8; journal:IEEE ELECTROMAGNETIC COMPATIBILITY MAGAZINE; https://hdl.handle.net/11566/331573; https://ieeexplore.ieee.org/document/10534244
DOI:
10.1109/memc.2024.10534244
Rights:
info:eu-repo/semantics/openAccess ; license:Tutti i diritti riservati ; license:Licenza specifica dell'editore ; license uri:iris.PRI01 ; license uri:iris.PRI02
Accession Number:
edsbas.A5A86258
Database:
BASE

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The analysis of stochastic electromagnetic fields is gaining more and more relevance due to the exponential growth of complex high-performance electronic systems. Stochastic electromagnetic fields are characterized by auto and cross-correlation functions which can be obtained from experimental data. Different methods have been proposed for the numerical propagation of correlation information within the near-field region of a stochastic radiator. As a guideline for general geometries, near-field Green's functions combined with the method of moments can be used for the numerical estimation of field correlations in the near-field surrounding a device under test. In the ray-tracing limit, a more insightful propagation method based on the Wigner transformation has been devised, through which it is also possible to estimate the propagation of stochastic fields in the near-field. In this paper we report on the implementation of the proposed guide in the open source Python programming language, accessible through the IEEE Standard Association repository to ensure the dissemination of the standard and encourage the development of new versions.