Design of phase-only reconfigurable planar array antenna in selected phi cuts using various meta-heuristic optimization algorithms

• Published in: Sadhana (Bangalore) Vol. 44; no. 4; pp. 1 - 8
• Main Authors: Jamunaa, D, Mahanti, G K, Hasoon Al Attar, Feras Nadhim
• Format: Journal Article
• Language: English
• Published: New Delhi Springer India 01.04.2019; Springer Nature B.V
• Subjects: Antenna arrays; Antennas; Computer simulation; Engineering; Evolutionary algorithms; Excitation; Fitness; Heuristic methods; Multiple objective analysis; Mutual coupling; Optimization; Optimization algorithms; Parameters; Pencil beams; Reconfiguration; Swarm intelligence; Synthesis; Artificial Bee Colony algorithm; Side Lobe Level; Imperialist Competitive algorithm; Phase-only reconfigurable array antenna; flat top beam; Moth–flame optimization algorithm
• ISSN: 0256-2499; 0973-7677
• DOI: 10.1007/s12046-019-1067-3

In this paper, a pattern synthesis based on a multiobjective optimization algorithm is proposed for the generation of a reconfigurable pencil/flat top dual-beam planar antenna array built using isotropic antenna elements in selected phi cuts. These beams claim the same amplitude excitations and differ from each other in phase excitations. Zero-phase excitations are used in pencil beam and these phases are updated with optimum phases for the flat top beam. All the excitations are obtained using Moth–flame optimization algorithm. With the support of the fitness functions, care is taken to control the expected values of the radiation pattern parameters to remain under certain fixed limit. In addition, synthesis is also done for the provision of a null in a particular direction for rejection of interference in the pencil beam in two different phi cuts. To suppress the mutual coupling effects, dynamic range ratio is kept under a threshold limit. Simulation results show the effectiveness of this proposed synthesis for phi cut planes. This algorithm is compared and proved to be better in many aspects over the standard meta-heuristic algorithms like Artificial Bee Colony and Imperialist Competitive algorithms in terms of performance parameters.