**Authors:** Krishna Naishadham and Jean E. Piou

**Source:** FERMAT, Volume 30, Article 1, Nov.-Dec., 2018

**Abstract:** As computing power and algorithmic advances have evolved significantly in the recent past, it is now feasible to solve complex electromagnetic (EM) problems involving scattering, radar cross section, antenna design, microwave circuit design, artificial EM materials, etc. using full-wave numerical methods. Several general-purpose commercial software packages are routinely used in industry in all these domains for EM analysis or design. However, the task of processing large sets of data output from these design studies and analyses is generally beyond the realm of commercial software packages, and the designer spends many hours writing problem-specific computer programs to extract the desired performance parameters. Determination of coupling coefficients or the unloaded quality factor of a dielectric resonator, de-embedding feed lines from antenna currents, removal of discontinuity effects, the extraction of equivalent circuit models, etc. are some examples where auxiliary processing is needed for the extraction of EM parameters of interest. The same considerations apply to the parametric analysis of measured data in the presence of noise. This paper presents a versatile data-driven spectral model derived from a state-space system representation of the computed or measured EM fields, from which all the parameters of interest can be extracted. Several examples will be presented to demonstrate the usefulness of the proposed approach for parametric extraction in EM problems.

**Index Terms:** Electromagnetic Scattering, Finite Difference Time Domain, Finite Integration Time Domain, Microwave Circuit, Microwave Resonator, Signal Extrapolation, Spectral Estimation, State Space Method, System Identification, Transient Analysis, Transmission Line

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