Synthesis of new antenna arrays with arbitrary geometries based on the superformula

The synthesis of antenna arrays with low sidelobe levels is needed to enhance the communication systems’ efficiency. In this paper, new arbitrary geometries that improve the ability of the antenna arrays to minimize the sidelobe level, are proposed. We employ the well-known superformula equation in the antenna arrays field by implementing the equation in the general array factor equation. Three metaheuristic optimization algorithms are used to synthesize the antenna arrays and their geometries; antlion optimization (ALO) algorithm, grasshopper optimization algorithm (GOA), and a new hybrid algorithm based on ALO and GOA. All the proposed algorithms are high-performance computational methods, which proved their efficiency for solving different real-world optimization problems. 15 design examples are presented and compared to prove validity with the most general standard geometry: elliptical antenna array (EAA). It is observed that the proposed geometries outperform EAA geometries by 4.5 dB and 10.9 dB in the worst and best scenarios, respectively, which proves the advantage and superiority of our approach

The optimal synthesis of scanned linear antenna arrays

In this paper, symmetric scanned linear antenna arrays are synthesized, in order to minimize the side lobe level of the radiation pattern. The feeding current amplitudes are considered as the optimization parameters. Newly proposed optimization algorithms are presented to achieve our target; Antlion Optimization (ALO) and a new hybrid algorithm. Three different examples are illustrated in this paper; 20, 26 and 30 elements scanned linear antenna array. The obtained results prove the effectiveness and the ability of the proposed algorithms to outperform and compete other algorithms like Symbiotic Organisms Search (SOS) and Firefly Algorithm (FA)