Improved line–line method for propagation constant measurement of reflection-asymmetric networks. (31st March 2022)

• Record Type: Journal Article
• Authors: Hasar, Ugur Cem; Ozturk, Hamdullah; Korkmaz, Huseyin; Izginli, Mucahit; Karaaslan, Muharrem
• Is Part Of: Measurement. Volume 192(2022)
• Publication Date: 2022-03-31
• Subjects: Line–line method -- Reflection-asymmetric network -- Propagation constant; Weights and measures -- Periodicals; Measurement -- Periodicals; Measurement; Weights and measures; Periodicals; 530.8
• DOI: 10.1016/j.measurement.2022.110848
• Languages: English
• ISSNs: 0263-2241

Abstract

Abstract: A new formalism using line–line measurements is proposed to improve the accuracy of propagation constant measurement of reflection-asymmetric networks using non-calibrated scattering (S-) parameters. For this measurement, the method uses a reference network with arbitrary forward and backward impedance, propagation constant, and length, thus giving flexibility in the application of line–line methods. S-parameter measurements were carried out for propagation constant extraction of a reflection-asymmetric waveguide loaded with a bianisotropic metamaterial slab made by C-shaped split-ring-resonators using two different kinds of reference networks (two empty waveguide sections as the first kind and the same sections loaded by polyethylene samples as the second kind). It is observed that the standard deviation in the extracted real part of the propagation constant of this network by our method could be reduced by using the first kind of reference network, indicating that the accuracy of our method could be improved using a suitable reference network. Highlights: A new formalism is proposed to determine propagation constant of networks with asymmetric reflections. The reference network can have arbitrary forward/backward impedance, propagation constant, and length. The new formalism allows flexibility in the application of line–line methods. Performance of our method could be improved using different reference networks.