Comparison of two optimization techniques for the estimation of complex permittivities of multilayered structures using waveguide measurements

In this paper, two separate techniques, i.e., sequential quadratic programming (SQP) and a genetic algorithm (GA), were used to estimate the complex permittivity of each layer in a multilayer composite structure. The relative performance of the algorithms was characterized by applying each algorithm to one of three different error functions. Computer generated S-parameter data sets were initially used in order to establish the achievable accuracy of each algorithm. Based on these data sets and S-parameter measurements of single and multilayer samples obtained using a standard X-band waveguide procedure, the GA was determined to be the more robust algorithm in terms of minimizing rms error of measured/generated and formulated S-parameters. The GA was found to perform exceptionally well for all cases considered, whereas SQP, although a more computationally efficient method, was somewhat limited for two error function choices due to local minima trapping.