Intelligent Design of Reconfigurable Microstrip Antenna Based on Adaptive Immune Annealing Algorithm

The application of intelligent algorithm in reconfigurable antenna design can break the inefficiency of traditional antenna design based on engineering experience and electromagnetic simulation software and can significantly improve the intelligent level of antenna design. However, the convergence rate, global search ability, and optimization accuracy of the intelligent algorithm seriously restrict the accuracy and automation efficiency of antenna design and have become the bottleneck of reconfigurable antenna rapid intelligent design. Therefore, an adaptive immune annealing algorithm (AIAA) for rapid design of reconfigurable antenna is proposed in this article. AIAA introduces the idea of adaptive crossover and mutation into the basic immune algorithm (IA), which improves its population update strategy and improves the convergence rate of the algorithm; moreover, simulated annealing (SA) operator is added to the improved IA, which enhances the global search ability of the algorithm. The standard function test results show that compared with the basic IA, AIAA improves the convergence rate, global search ability, optimization accuracy, and robustness. Finally, based on AIAA, a design scheme of frequency and pattern reconfigurable antenna is proposed. Frequency reconfigurable antennas with resonant frequencies of 8.58 GHz (
$X$
-band) and 15.83 GHz (
Ku
-band) and pattern reconfigurable antennas with maximum radiation directions of +39° and −39° in the
xoz
plane are designed based on this design method, and experimental tests are carried out. The accuracy and effectiveness of the AIAA in the design of reconfigurable microstrip antenna are verified.