Generalized Formulation of Response Features for Reliable Optimization of Antenna Input Characteristics

Electromagnetic (EM)-driven parameter adjustment has become imperative in the design of modern antennas. It is necessary because the initial designs rendered through topology evolution, parameter sweeping, or theoretical models are often of poor quality and need to be improved to satisfy stringent performance requirements. Given multiple objectives, constraints, and a typically large number of geometry parameters, the design closure should be carried out through numerical optimization. Unfortunately, standard algorithms entail high CPU expenses and are prone to failure. Feature-based optimization (FBO) is one of the methods developed to alleviate these difficulties by reformulating the design task in terms of the characteristic points extracted from EM-simulated responses. FBO capitalizes on a less nonlinear relationship between the feature point coordinates and antenna dimensions as compared to the original responses (e.g., frequency characteristics). This leads to flattening the functional landscape to be handled, faster convergence of the optimization algorithms, and a possibility of mitigating the issues pertinent to multimodality. Notwithstanding, the response features have to be individually defined for each type of antenna response and tailored to a particular type of design specifications. This requires user experience and hinders the widespread application of FBO. This article proposes a generalized and unified feature point definition, which is suitable for the majority of typical antenna input characteristics (narrowband, multiband, enhanced bandwidth, and wideband) and performance specifications (matching improvement, bandwidth enhancement, and a mixture thereof). Our framework allows for an automated definition of the feature points given the performance specifications, along with their extraction from EM-simulated responses. The operation of the framework is illustrated using a range of planar antennas and favorably compared to conventional (nonfeature-based) design closure task formulation.