Comparison and Application of Two Approaches Extracting Equivalent Dipole Arrays of an IC from Measured Near-Field Magnitude Data

Kwak, Kyungjin; Kim, Jingook; Bae, Tae-il; Hong, Kichul; Kim, Hyungsoo

doi:10.1109/edaps.2018.8680902

Cited by 2 publications

(2 citation statements)

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“…As shown in Fig.3, the field distribution can be calculated as the superposition of field created by the dipoles and their images. Therefore, the detailed expressions of T PzEz , T MxEz , T MyEz T PzHx , T MxHx , T MyHx , T PzHy , T MxHy and T MyHy are given as (10) - (18). To simplify the equations, the expansions of terms f 1 (d) and f 2 (d) are given as (19) and (20), respectively.…”

Section: New Transfer Model and Inverse Problemmentioning

confidence: 99%

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An Improved Equivalent Dipole Moment Source Model Based on Regularization Optimization Method for Near Field-Far Field Conversion

et al. 2020

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The radiation emission from high-speed digital circuit may result in radio-frequency interference (RFI) problems in modern electronic devices. In this paper, an improved equivalent dipole source based on a new transfer model and a new regularization method is proposed. The equivalent source is obtained by solving an inverse equation with near-field data. The tangential component of electric field used in conventional equivalent source extraction is replaced by the normal component, which can reduce the test difficulty and enhance the measurement efficiency. The new regularization method based on Tikhonov and truncated singular value decomposition (TSVD) can enhance the stability and accuracy of the dipole solution. In addition, the new transfer model and regularization method are verified by simulations and measurements.

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Section: New Transfer Model and Inverse Problemmentioning

confidence: 99%

“…Previous work has shown that this approach can be applied in near-field coupling and far-field radiation of ICs, packages and PCBs [17]. And the research tendency of equivalent dipole source is using less nearfield data to enhance the measurement efficient of near-field data [18].…”

Section: Introductionmentioning

confidence: 99%