Title page for ETD etd-08082007-120136

Type of Document Dissertation
Author Fidanboylu, Kemal M.
URN etd-08082007-120136
Title Time domain synthesis applied to modeling of microwave structures and material characterization
Degree PhD
Department Electrical Engineering
Advisory Committee
Advisor Name Title
Riad, Sedki Mohamed Committee Chair
Besieris, Ioannis M. Committee Member
Elshabini-Riad, Aicha A. Committee Member
Herdman, Terry L. Committee Member
Vanlandingham, Hugh F. Committee Member
  • Microwave devices
Date of Defense 1991-05-15
Availability restricted

In this dissertation a new time domain approach for the determination of material properties such as the complex permittivity and the complex permeability in a stripline geometry is presented. The new technique uses both Time Domain Reflectometry (TDR) and Time Domain Transmission (TDT) measurements for determining an optimum frequency dependent lossy transmission line model for the stripline under test. The optimization is done in the time domain by comparing the experimental TDR and TDT response waveforms with the simulated ones using a non-linear least squares fit. The conventional optimization algorithms have shown to be inefficient in this specific application. In this dissertation an efficient optimization algorithm which has been developed to suit this application is also presented. In general, the material properties in a stripline under test are related with the geometrical parameters of the line through complicated integral expressions. Using the proposed approach, the use of complicated integral expressions are avoided. The material properties such as the complex permittivity and the complex permeability are determined from the optimum lossy transmission line model. For this purpose, the frequency behavior of the line parameters have to be known beforehand in the form of causal mathematical models. The literature survey shows that, no causal model exists for the complex permittivity of thick film and polymer materials. The dissertation proposes a new causal model for this purpose.

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