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Q-Factor Estimation From the Return Loss of Low-Q Microwave Resonators

Title data

Królak, Radoslaw ; Fischerauer, Gerhard:
Q-Factor Estimation From the Return Loss of Low-Q Microwave Resonators.
In: IEEE Transactions on Microwave Theory and Techniques. Vol. 64 (November 2016) Issue 11 . - pp. 3797-3808.
ISSN 0018-9480
DOI: https://doi.org/10.1109/TMTT.2016.2605673

Abstract in another language

We propose a novel approach for evaluating the resonance curves of low- Q microwave resonators, which are associated with the in situ monitoring of large and lossy material samples in cavities. It is assumed that the process observed is stationary and thus admits measurements over long enough time intervals to produce statistical data on selected features of the resonance curve. These features, such as resonance frequency and half-power bandwidth, are random variables owing to process and measurement noise. We show by numerical experiments and by measurements that the Q -factor of the resonator can be extracted from the probability density function (pdf) of the random variable “resonance frequency” or even from only a single moment of the pdf. This is demonstrated by way of the standard deviation (the square root of the second central moment), which, in practice, is estimated from the empirical standard deviation or measurement uncertainty. The method can be applied to lower Q-factors than any other method to date.

Further data

Item Type: Article in a journal
Refereed: Yes
Keywords: Microwave measurement; frequency measurement; resonant frequency; microwave circuits; cavity resonators; Q-factor; low-Q; stochastic processes; statistics
Institutions of the University: Faculties
Faculties > Faculty of Engineering Science
Faculties > Faculty of Engineering Science > Chair Measurement and Control Technology
Faculties > Faculty of Engineering Science > Chair Measurement and Control Technology > Chair Measurement and Control Technology - Univ.-Prof. Dr.-Ing. Gerhard Fischerauer
Result of work at the UBT: Yes
DDC Subjects: 600 Technology, medicine, applied sciences > 620 Engineering
Date Deposited: 14 Nov 2016 08:08
Last Modified: 14 Nov 2016 08:09
URI: https://eref.uni-bayreuth.de/id/eprint/35117