An Optimal Elliptical Antenna Array Design Using Novel Meta-heuristic Optimization Approaches

In this study, elliptical antenna arrays (EAAs) with low maximum side lobe levels (MSLs) and fixed half-power beam width has been synthesized with novel meta-heuristic methods, namely, Archimedes Optimization Algorithm (AOA) and Chimp Optimization Algorithm (ChOA). In order to use the communication systems effectively and efficiently in recent years, application-specific antenna designs have become more important. In this specialization in wireless communication, interest in the optimum design of EAA specially designed for the application has increased. Two different cases are discussed in this study. In the first case, the angular position of the EAA elements are fixed and the amplitude values are optimally determined by AOA and ChOA methods to obtained radiation patterns with reduced MSLs. Assuming that the elements in the antenna array are fed uniformly and the current amplitude values are all one, the angular positions of the elements are found by the proposed novel optimization methods to minimize MSLs in the second case. To test the flexibility and performance of the proposed methods, three different designs of the 8, 12 and 20 elements EAA are considered. The results of the AOA and ChOA methods are compared with the current results obtained by Antlion Optimisation and Symbiotic Organisms Search in the literature. In addition, the statistical performances of the proposed methods are compared. It has been observed that generally the results obtained with the AOA method are better than other compared methods.