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Article
Extraction of Dispersive Material Parameters Using Vector Network Analyzers and Genetic Algorithms
Proceedings of the IEEE Instrumentation and Measurement Technology Conference, 2006
  • Jianmin Zhang
  • Marina Koledintseva, Missouri University of Science and Technology
  • David Pommerenke, Missouri University of Science and Technology
  • James L. Drewniak, Missouri University of Science and Technology
  • Konstantin Rozanov, Missouri University of Science and Technology
  • Antonio Orlandi
  • G. Antonini
Abstract
A novel method to extract dispersive properties for dielectrics over a wide frequency range is proposed. This method is based on measuring scattering parameters for planar transmission lines and applying genetic algorithms. The scattering parameters are converted into ABCD matrix parameters. The complex propagation constant of the TEM wave inside the line is obtained from A-parameters of the ABCD matrix. For planar transmission lines, analytical or empirical formulas for dielectric loss, conductor loss, and phase constant are known. The genetic algorithm is then used to extract the Debye parameters for the dielectric substrates. FDTD modeling is used to verify the dispersive parameter extraction by comparing with the measurement.
Meeting Name
IEEE Instrumentation and Measurement Technology Conference, 2006
Department(s)
Electrical and Computer Engineering
Second Department
Physics
Keywords and Phrases
  • Debye Dispersion Law,
  • S-Parameter Measurement,
  • Conduction Loss,
  • Dielectric Loss,
  • Planar Structure Transmission Lines
Library of Congress Subject Headings
enetic algorithms
Document Type
Article - Conference proceedings
Document Version
Final Version
File Type
text
Language(s)
English
Rights
© 2006 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.
Publication Date
1-1-2006
Citation Information
Jianmin Zhang, Marina Koledintseva, David Pommerenke, James L. Drewniak, et al.. "Extraction of Dispersive Material Parameters Using Vector Network Analyzers and Genetic Algorithms" Proceedings of the IEEE Instrumentation and Measurement Technology Conference, 2006 (2006)
Available at: http://works.bepress.com/david-pommerenke/112/