A Novel Multi-Objective Maxwell’s Equations Derived Optimization Algorithm and Application in Sparse Antenna Array Synthesis

Planar sparse array synthesis plays a critical role in modern radar and wireless communication systems. However, it remains challenging to simultaneously minimize the number of antenna elements while maintaining a low peak sidelobe level. Inspired by typical electromagnetic compatibility (EMC) phenomena, we previously developed the Maxwell’s Equations Derived Optimization (MEDO) algorithm, which enables accurate and robust solutions for complex electromagnetic optimization problems. In this paper, we extend MEDO to a multi-objective version (MO-MEDO), by incorporating non-dominated sorting with elitism and an external archive mechanism for Pareto front preservation. The proposed MO-MEDO algorithm exhibits excellent performance in sparse planar array synthesis, effectively achieving a favorable trade-off between array sparsity and sidelobe suppression.