Research on Antenna Multi-objective Optimization Method Based on Improved Immune Algorithm and HFSS Co-simulation

Due to the issues of insignificant optimization effects and low efficiency of HFSS electromagnetic simulation software in the process of antenna structure parameter optimization, this paper proposes an antenna multi-objective optimization method based on improved immune algorithm and HFSS joint simulation. For an end-loaded bent dipole antenna, four objective functions are proposed: small offset between the center frequency and the target frequency, low return loss, impedance matching, and high gain. The immune algorithm is improved by generating the initial population from SPM chaotic map, calculating affinity by standardized Euclidean distance, and adopting adaptive recombination and mutation probability. MATLAB-HFSS-API is used to achieve joint simulation and multi-objective optimization of antenna structure parameters. The example verification shows that the improved immune algorithm has strong optimization capabilities, and the optimization results of the tag antenna structure parameters obtained can meet the optimization target requirements to a greater extent. The optimization time is only 32.5% of the HFSS electromagnetic simulation software, and the antenna optimization design efficiency is significantly improved.