A Practical De-Embedding Error Analysis Method based on Statistical Circuit Models of Fixtures

Shaohui Yong; Yuanzhuo Liu; Han Gao; Scott Hinaga; Soumya De; Darja Padilla; Douglas Yanagawa; James L. Drewniak; Victor Khilkevich

doi:10.1109/ISEMC.2019.8825291

A Practical De-Embedding Error Analysis Method based on Statistical Circuit Models of Fixtures

Shaohui Yong
, Yuanzhuo Liu
, Han Gao
, Scott Hinaga
, Soumya De
, Darja Padilla
, Douglas Yanagawa
, James L. Drewniak
, Victor Khilkevich

Electrical and Computer Engineering

Research output: Contribution to journal › Article › peer-review

Abstract

De-embedding methods require multiple identical fixtures. However, in reality the fixtures cannot be fabricated perfectly identical due to manufacturing variations. The identical assumptions for de-embedding algorithm will be unavoidably violated, which is going to introduce error due to de-embedding. In this paper, a novel methodology is proposed to estimate the error due to de-embedding for practical testing vehicle measurement. Models of the Thru and Total lines with fixtures are created. Perturbation in the fixtures is introduced based on TDR measurements. The confidence interval of the de-embedded insertion loss is obtained after statistical analysis assuming the variations among fixtures are subjected to Gaussian distribution.

Original language	American English
Journal	Proceedings of the 2019 IEEE International Symposium on Electromagnetic Compatibility, Signal and Power Integrity (2019, New Orleans, LA)
DOIs	https://doi.org/10.1109/ISEMC.2019.8825291
State	Published - Jul 1 2019

Keywords

2X-Thru
De-Embedding
Statistical Simulation
Transmission Line Measurements
TRL

Disciplines

Electrical and Computer Engineering

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10.1109/ISEMC.2019.8825291License: CC BY

https://doi.org/10.1109/ISEMC.2019.8825291

Cite this

Yong, S., Liu, Y., Gao, H., Hinaga, S., De, S., Padilla, D., Yanagawa, D., Drewniak, J. L., & Khilkevich, V. (2019). A Practical De-Embedding Error Analysis Method based on Statistical Circuit Models of Fixtures. Proceedings of the 2019 IEEE International Symposium on Electromagnetic Compatibility, Signal and Power Integrity (2019, New Orleans, LA). https://doi.org/10.1109/ISEMC.2019.8825291

Yong, S, Liu, Y, Gao, H, Hinaga, S, De, S, Padilla, D, Yanagawa, D, Drewniak, JL & Khilkevich, V 2019, 'A Practical De-Embedding Error Analysis Method based on Statistical Circuit Models of Fixtures', Proceedings of the 2019 IEEE International Symposium on Electromagnetic Compatibility, Signal and Power Integrity (2019, New Orleans, LA). https://doi.org/10.1109/ISEMC.2019.8825291

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title = "A Practical De-Embedding Error Analysis Method based on Statistical Circuit Models of Fixtures",

abstract = " De-embedding methods require multiple identical fixtures. However, in reality the fixtures cannot be fabricated perfectly identical due to manufacturing variations. The identical assumptions for de-embedding algorithm will be unavoidably violated, which is going to introduce error due to de-embedding. In this paper, a novel methodology is proposed to estimate the error due to de-embedding for practical testing vehicle measurement. Models of the Thru and Total lines with fixtures are created. Perturbation in the fixtures is introduced based on TDR measurements. The confidence interval of the de-embedded insertion loss is obtained after statistical analysis assuming the variations among fixtures are subjected to Gaussian distribution.",

keywords = "2X-Thru, De-Embedding, Statistical Simulation, Transmission Line Measurements, TRL",

author = "Shaohui Yong and Yuanzhuo Liu and Han Gao and Scott Hinaga and Soumya De and Darja Padilla and Douglas Yanagawa and Drewniak, \{James L.\} and Victor Khilkevich",

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doi = "10.1109/ISEMC.2019.8825291",

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AU - Yong, Shaohui

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AU - De, Soumya

AU - Padilla, Darja

AU - Yanagawa, Douglas

AU - Drewniak, James L.

AU - Khilkevich, Victor

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N2 - De-embedding methods require multiple identical fixtures. However, in reality the fixtures cannot be fabricated perfectly identical due to manufacturing variations. The identical assumptions for de-embedding algorithm will be unavoidably violated, which is going to introduce error due to de-embedding. In this paper, a novel methodology is proposed to estimate the error due to de-embedding for practical testing vehicle measurement. Models of the Thru and Total lines with fixtures are created. Perturbation in the fixtures is introduced based on TDR measurements. The confidence interval of the de-embedded insertion loss is obtained after statistical analysis assuming the variations among fixtures are subjected to Gaussian distribution.

AB - De-embedding methods require multiple identical fixtures. However, in reality the fixtures cannot be fabricated perfectly identical due to manufacturing variations. The identical assumptions for de-embedding algorithm will be unavoidably violated, which is going to introduce error due to de-embedding. In this paper, a novel methodology is proposed to estimate the error due to de-embedding for practical testing vehicle measurement. Models of the Thru and Total lines with fixtures are created. Perturbation in the fixtures is introduced based on TDR measurements. The confidence interval of the de-embedded insertion loss is obtained after statistical analysis assuming the variations among fixtures are subjected to Gaussian distribution.

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KW - Transmission Line Measurements

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JO - Proceedings of the 2019 IEEE International Symposium on Electromagnetic Compatibility, Signal and Power Integrity (2019, New Orleans, LA)

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ER -

A Practical De-Embedding Error Analysis Method based on Statistical Circuit Models of Fixtures

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Keywords

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