Non-uniform concentric elliptical antenna array synthesis using adaptive evolutionary multi-objective optimization

The synthesis of antenna arrays with minimized sidelobes and reduced structural complexity is a fundamental challenge in the areas of modern electromagnetic designs. This research presents a comprehensive framework for the effective synthesis of non-uniform concentric elliptical antenna arrays by considering the simultaneous suppression of peak sidelobe level and total number of active array elements. Unlike the conventional elliptical array antenna studies which assume fixed geometries and fixed elemental counts, the proposed formulation integrates controllable-eccentricity, nonuniform angular-distribution, and discrete array element activation within a rigorous multi-objective optimization structure. A generalized analytical array factor model for sparse-concentric elliptical-configurations is developed. An adaptive evolutionary multi-objective algorithm with diversity driven parameter control is employed to explore the mixed discrete–continuous search space efficiently. Extensive simulations demonstrate that the proposed approach accomplishes deeper sidelobe minimization with fewer array elements as compared to the recent elliptical and concentric array synthesis approaches. Statistical performance-evaluation confirms improved convergence stability and robustness. The results establish that controlled geometric eccentricity can compensate for elemental array reduction, leading to compact and high-performance array structures suitable for advanced wireless and radar systems.