A Particle Swarm Optimization Method for Optimization Design of Geometric Parameters on Microstrip Patch Antenna

Antenna design optimization aims at finding the antenna meeting multiple performance goals by adjusting various parameters of the antenna. At present, most antenna design optimization methods require antenna engineers to perform repeated parameter scanning and manual adjustments after optimization to obtain an antenna that meets the required performance goals. This paper presents a Latin Hypercube Sampling Particle Swarm Optimization (LHS-PSO) method suitable for geometric optimization of microstrip patch antenna. In this proposed method, representative samples are generated by the Latin hypercube sampling method, and used as the initial particle swarm. Subsequently, this work considers to use the actual frequency range of the antenna and the specified frequency range to design the fitness function of the particle swarm optimization method. Then the method updates the particles to obtain the geometric parameters of the microstrip patch antenna within the specified frequency range. The results show that this method can obtain a microstrip patch antenna that meets the specified frequency range and costs less than scanning parameters and manual adjustment of parameters, and has a good optimization design effect.