Reflection type Q-factor measurement using standard least squares methods
Article
Article Title | Reflection type Q-factor measurement using standard least squares methods |
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ERA Journal ID | 5066 |
Article Category | Article |
Authors | Shahid, S. (Author), Ball, J. A. R. (Author), Wells, C. G. (Author) and Wen, P. (Author) |
Journal Title | IET Microwaves, Antennas and Propagation |
Journal Citation | 5 (4), pp. 426-432 |
Number of Pages | 7 |
Year | 2011 |
Place of Publication | Stevenage, Herts, United Kingdom |
ISSN | 1350-2417 |
1751-8725 | |
1751-8733 | |
Digital Object Identifier (DOI) | https://doi.org/10.1049/iet-map.2010.0395 |
Web Address (URL) | http://www.ietdl.org/dbt/dbt.jsp?KEY=IMAPCH&Volume=5&Issue=4 |
Abstract | Methods to determine resonant cavity Q-factor from vector network analyser reflection data are often quite complex. This study presents a simple method which makes use of two least squares algorithms applied sequentially. Firstly, a circle is fitted to the data, which is then projected onto a linear frequency scale using the Ginzton technique. A straight line is fitted to the projected data, and the loaded Q-factor and the resonant frequency are obtained from the line coefficients. The method has been tested on both synthetic and experimental data, and compared with the Kajfez QZERO software, and the results are shown to be accurate to a fraction of 1%. |
Keywords | Q-factor; reflection; least squares |
ANZSRC Field of Research 2020 | 490101. Approximation theory and asymptotic methods |
400801. Circuits and systems | |
400899. Electrical engineering not elsewhere classified | |
Public Notes | Files associated with this item cannot be displayed due to copyright restrictions. |
Byline Affiliations | Department of Electrical, Electronic and Computer Engineering |
Institution of Origin | University of Southern Queensland |
https://research.usq.edu.au/item/q0q11/reflection-type-q-factor-measurement-using-standard-least-squares-methods
2018
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