Abstract
In this paper, a novel hybrid iterative algorithm based on imperial competition algorithm (ICA) and Ant Colony Optimization (ACO) is proposed to achieve multi-parameters unified-optimization of millimeter wave (mmWave) microstrip antenna. After assimilation of ICA, the pheromone guidance mechanism is added to update the position of ant, which avoids the ICA solution falling into a local optimum. Two input impedance models of microstrip antenna are solved by different algorithms, which show the proposed algorithm (ICACO) converges faster than three compared algorithms. The multi-parameters unified-optimization of mmWave microstrip antenna under the operation of TM 10 and TM 02 modes is carried out by ICACO to enhance impedance bandwidth and improve bore-sight gain. The proposed algorithm is applicable in antenna multi-parameters design problems as a reliable approach with faster convergence rate.
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