Shahid, S. and Ball, J. A. R. and Wells, C. G. and Wen, P. (2011) Reflection type Q-factor measurement using standard least squares methods. IET Microwaves, Antennas and Propogation, 5 (4). pp. 426-432. ISSN 1751-8725
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%.
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Item Type: | Article (Commonwealth Reporting Category C) |
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Refereed: | Yes |
Item Status: | Live Archive |
Additional Information: | Permanent restricted access to paper due to publisher copyright policy. |
Faculty/School / Institute/Centre: | Historic - Faculty of Engineering and Surveying - Department of Electrical, Electronic and Computer Engineering (Up to 30 Jun 2013) |
Faculty/School / Institute/Centre: | Historic - Faculty of Engineering and Surveying - Department of Electrical, Electronic and Computer Engineering (Up to 30 Jun 2013) |
Date Deposited: | 19 Apr 2011 00:36 |
Last Modified: | 24 Aug 2014 23:22 |
Uncontrolled Keywords: | Q-factor; reflection; least squares |
Fields of Research (2008): | 01 Mathematical Sciences > 0102 Applied Mathematics > 010201 Approximation Theory and Asymptotic Methods 09 Engineering > 0906 Electrical and Electronic Engineering > 090601 Circuits and Systems 09 Engineering > 0906 Electrical and Electronic Engineering > 090699 Electrical and Electronic Engineering not elsewhere classified |
Socio-Economic Objectives (2008): | E Expanding Knowledge > 97 Expanding Knowledge > 970109 Expanding Knowledge in Engineering |
Identification Number or DOI: | https://doi.org/10.1049/iet-map.2010.0395 |
URI: | http://eprints.usq.edu.au/id/eprint/18852 |
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