研究目的
Investigating the stability and well-posedness of the inverse problem of reconstructing the real value of the permittivity of a dielectric layer in a rectangular waveguide using the least squares method from multi-frequency measurement data.
研究成果
The study proves the stability and convergence of multi-frequency least squares method for reconstructing permittivity of the layer in a metal waveguide from the transmission coefficient of a principal mode. Appropriate estimates show that the solution accuracy increases when optimal measurement parameters are chosen.
研究不足
The problem of determining the dielectric constant of a dielectric inclusion from the elements of the scattering matrix or the transmission coefficient of the principal mode is generally unsolvable because the range of the function to be inverted forms a set of measure zero on the complex plane. Additionally, the occurrence of self-intersections of the parametric curve leads to non-uniqueness of the solution to the inverse problem.
1:Experimental Design and Method Selection:
The study uses the solution to Maxwell’s equations in a rectangular single-mode waveguide with multi-mode boundary conditions to determine the parameters of the inclusion. The well-posedness of the inverse problem is studied using explicit expressions for the S-parameters of the waveguide when the inclusion is a plane-parallel dielectric slab.
2:Sample Selection and Data Sources:
The study considers the transmission coefficient of the principal mode of an electromagnetic wave in a single-mode metal waveguide scattered by the dielectric layer.
3:List of Experimental Equipment and Materials:
The study involves a standard rectangular waveguide with a dielectric inclusion (a layer).
4:Experimental Procedures and Operational Workflow:
The study involves measuring the transmission coefficient of the principal mode and applying the least squares method to reconstruct the permittivity of the dielectric layer from multi-frequency measurement data.
5:Data Analysis Methods:
The study uses the method of least squares for data analysis and provides estimates of the accuracy of the approximate solution.
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