A Surrogate Modeling Approach for Frequency-Reconfigurable Antennas

A novel generalizable surrogate modeling approach is specifically developed for frequency-reconfigurable antennas. The generalizable modeling processes is based on the rigorous mathematical derivation, including the solution of a nonlinear overdetermined system, the optimization in the complex field, and the interpolation in multidimensional continuous space. As a postprocessing method, the approach can convert the discrete data of CAD simulation to a surrogate model. Subsequently, a reconfigurable UWB antenna with a tunable notch band is taken as an example to demonstrate that the surrogate modeling approach is feasible, effective, and precise. It also has the flexible ability to adapt to strict requirements and complicated scenarios. The proposed surrogate model is a good candidate for the interface standard between a reconfigurable antenna and signal processing part in a cognitive radio (CR) system.

Automated summary

A novel surrogate modeling approach for frequency-reconfigurable antennas is proposed, based on rigorous mathematical derivation. The approach converts discrete data from CAD simulation into a surrogate model through nonlinear overdetermined system solution, complex field optimization, and multidimensional continuous space interpolation. The feasibility, effectiveness, and precision of the approach are demonstrated using a reconfigurable UWB antenna with a tunable notch band as an example. The proposed surrogate model is flexible and can meet strict requirements in complex scenarios, making it a good candidate for the interface standard between a reconfigurable antenna and signal processing part in a cognitive radio system.