Establishing Traceability of an Electronic Calibration Unit Using the NIST Microwave Uncertainty Framework

被引：0

作者：

Jargon, Jeffrey A. ^{[1
]}

Williams, Dylan F. ^{[1
]}

Wallis, T. Mitch ^{[1
]}

LeGolvan, Denis X. ^{[1
]}

Hale, Paul D. ^{[1
]}

机构：

[1] Natl Inst Stand & Technol, Boulder, CO 80305 USA

来源：

2012 79TH ARFTG MICROWAVE MEASUREMENT CONFERENCE (ARFTG) | 2012年

关键词：

Electronic calibration unit; traceability; uncertainty; vector network analyzer; NETWORK-ANALYZER CALIBRATION;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

We present a method for establishing traceability of a commercial electronic calibration unit for vector network analyzers by characterizing the scattering parameters of its internal states with repeated multiline thru-reflect-line (TRL) calibrations and utilizing the NIST Microwave Uncertainty Framework to propagate uncertainties. With the electronic calibration unit characterized, we use it to calibrate a network analyzer, and characterize a number of verification devices with corresponding uncertainties. We also characterize the same verification devices using one of the previous multiline TRL calibrations, and compare results.

引用

页数：5

共 17 条

[1] Developing Models for a 0.8 mm Coaxial VNA Calibration Kit within the NIST Microwave Uncertainty Framework
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[6] Three-Port Vector-Network-Analyzer Calibrations using the NIST Microwave Uncertainty Framework
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[J]. 2019 92ND ARFTG MICROWAVE MEASUREMENT CONFERENCE (ARFTG), 2019,
[7] Physical Models for 2.4 mm and 3.5 mm Coaxial VNA Calibration Kits Developed within the NIST Microwave Uncertainty Framework
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[J]. 2015 85TH ARFTG MICROWAVE MEASUREMENT CONFERENCE, 2015,
[8] Characterizing a Noninsertable Directional Device Using the NIST Uncertainty Framework
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[J]. 2014 83RD ARFTG MICROWAVE MEASUREMENT CONFERENCE (ARFTG): MICROWAVE MEASUREMENTS FOR EMERGING TECHNOLOGIES, 2014,
[9] Uncertainty Analysis of Scattering Parameters Calibrated by an Electronic Calibration Unit Based on a Residual Model
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[J]. IEEE ACCESS, 2022, 10 : 6328 - 6337
[10] Calibration of a distributed flood forecasting model with input uncertainty using a Bayesian framework
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[J]. WATER RESOURCES RESEARCH, 2012, 48

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