Hybrid optimization model for design and optimization of microstrip patch antenna

The antenna design for a specified resonant frequency necessitates the computation of optimal values of different sizes. This is a harder task for microstrip patch antenna (MPA) since there is no precise numerical formula that leads to accurate solutions for designing these antennas. Presently, bio‐inspired approaches are widely deployed in numerous antenna designs and it has revealed an immense assurance in handling the rising necessities of antenna engineering for overall cost, reduced size, and enhanced performances. This work aims to introduce an optimal MPA design, where the antenna elements like patch length, patch height, substrate width, and substrate length are optimally tuned by a new hybrid optimization model. For this, a new hybridized model known as shark smell integrated EHO is proposed. Eventually, the primacy of the suggested model is scrutinized via varied assessments. Generally, microstrip patch antenna (MPA) encompasses a ground plane as well as a control patch. A substrate is available at the middle that reveals the accurate value of the dielectric constant. Typically, patch sizes are small when compared to the substrate and ground. On designing an MPA, a dielectric medium and resonance frequency are chosen to depend upon the dimension of MPA. Consequently, to develop the antenna performances, it is required to have a dielectric substrate, in which the effectiveness is made superior with higher radiation and bandwidth. The image discloses the method of MPA radiation.