Evaluation of mismatch uncertainty in microwave power sensor calibration using Monte-Carlo method

Wu, Thomas Y.; Chua, S.W.

doi:10.1109/imtc.2009.5168433

Cited by 3 publications

(12 citation statements)

References 8 publications

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“…In order to validate the developed software, we repeated simulations carried out in the publication [9] using the MCM and the results obtained were in agreement with those presented in [9]. The part of the calculation related to the GUM was performed using the open-access software METAS UncLib [10].…”

Section: Introductionmentioning

confidence: 58%

“…Publication [9] presents a comparison of results of determining the limit values of type A measurement uncertainty (caused by a random error from the mating connectors) for the mismatch factor 𝑀 obtained by the GUM and the MCM during the calibration of the RF power sensor. Measurements performed made in the system shown in Fig.…”

Section: Validation Of MCM Software By Comparison With Previously Pub...mentioning

confidence: 99%

“…where Γ S , Γ D , Γ G are, respectively, the reflection coefficients of the standard sensor, the DUT sensor, and the equivalent source of power splitter, which can be obtained from the conventional one-port VNA calibration method [13,15], or calculated from the expression [9]:…”

Section: Validation Of MCM Software By Comparison With Previously Pub...mentioning

confidence: 99%

“…Due to a discrepancy between the results obtained by the GUM and the MCM of estimating the calibration uncertainty of RF power sensors, which was pointed out in [9] but without explaining the reasons for the discrepancy, we carried out a detailed analysis, presented in Section 3, showing that the reason was nonlinearity of the measurement function 𝑌 = 𝑓 (𝑋 1 , . .…”

Section: Introductionmentioning

confidence: 99%

“…, 𝑋 𝑁 ). Measurements of similar type as presented in [9] are used at the LMEEiO for calibration of RF power sensors.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Determination of measurement uncertainty by a Monte Carlo method for an RF power sensor calibration system using a VNA

Jaworski,

Szatkowski,

Kossek

2023

Metrology and Measurement Systems

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This work proposes a systematic assessment of measuring type A uncertainty (caused by random errors) used in RF power sensor calibration. To reduce A type uncertainty, several successive measurements are repeated. The uncertainty arises from repeatability errors in connectors caused by changes in their electrical properties during repeated mating. The suitability of the METAS UncLib software was analysed and we concluded that software should be developed to take into account the shape of probability density function (PDF) using a Monte Carlo method (MCM), which was lacking in METAS UncLib. The self-developed software was then tested on an example taken from the literature and the superiority of the MCM over the analytical method (GUM) was confirmed. During the calibration of the RF sensor using a vector network analyzer (VNA), a series of repeated measurements were performed and, after applying our MCM software, it was found that the measurement uncertainties calculated by the MCM method were several times larger than those by the GUM. The reason for this was that the correlation between the measured input quantities was not taken into account. When this was done using a covariance matrix and assuming a normal PDF of the input quantities, the results obtained with the GUM and the MCM converged. Our main objective was to investigate the influence of the PDF shape of the input measurement samples on the measurement uncertainty. Taking more than a dozen measurements is too costly, on the other hand, the small sample size prevents a reliable determination of the PDF shape. Finally, to overcome this inconvenience, we have developed a special method that uses the histograms of standardized input data taken at all measurement frequencies under fixed conditions without disconnecting the connectors, to increasing the total number of results which were needed to create the PDF histograms of input quantities.

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Section: Introductionmentioning

confidence: 58%

Section: Validation Of MCM Software By Comparison With Previously Pub...mentioning

confidence: 99%

Section: Validation Of MCM Software By Comparison With Previously Pub...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…, 𝑋 𝑁 ). Measurements of similar type as presented in [9] are used at the LMEEiO for calibration of RF power sensors.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Determination of measurement uncertainty by a Monte Carlo method for an RF power sensor calibration system using a VNA

Jaworski,

Szatkowski,

Kossek

2023

Metrology and Measurement Systems

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show abstract

Research of Time-domain Model of Microwave Radiation Field Measurement System Based on Scatter Parameters Transient Analysis

Cheng

Jiang

Yao

et al. 2019

2019 PhotonIcs &Amp; Electromagnetics Research Symposium - Spring (PIERS-Spring)

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A Method for Generating a Sample of Two Uniformly Distributed Random Variables With Prescribed Coefficient of Correlation

Novaković

Pejic

Grbic

et al. 2021

IEEE Trans. Instrum. Meas.

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Evaluation of mismatch uncertainty in microwave power sensor calibration using Monte-Carlo method

Cited by 3 publications

References 8 publications

Determination of measurement uncertainty by a Monte Carlo method for an RF power sensor calibration system using a VNA

Determination of measurement uncertainty by a Monte Carlo method for an RF power sensor calibration system using a VNA

Research of Time-domain Model of Microwave Radiation Field Measurement System Based on Scatter Parameters Transient Analysis

A Method for Generating a Sample of Two Uniformly Distributed Random Variables With Prescribed Coefficient of Correlation

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