Sidelobe‐level suppression for linear and circular antenna arrays via the cuckoo search–chicken swarm optimisation algorithm. Issue 2 (1st January 2017)

• Record Type: Journal Article
• Authors: Liang, Shuang; Feng, Tie; Sun, Geng
• Is Part Of: IET microwaves, antennas & propagation. Volume 11:Issue 2(2017)
• Page Start: 209
• Page End: 218
• Publication Date: 2017-01-01
• Subjects: linear antenna arrays -- search problems -- antenna radiation patterns -- optimisation; sidelobe‐level suppression -- cuckoo search‐chicken swarm optimisation algorithm -- SLL suppression -- reliability -- communication system -- CSCSO -- LAA -- CAA -- linear antenna array -- circular antenna array -- chaos theory -- Levy flight weight coefficient -- radiation pattern optimisation -- particle swarm optimisation algorithm; Microwaves -- Periodicals; Microwave antennas -- Periodicals; Antennas (Electronics) -- Periodicals; Radio wave propagation -- Periodicals; Microwave communication systems -- Periodicals; 621.381305
• DOI: 10.1049/iet-map.2016.0083
• Languages: English
• ISSNs: 1751-8725

Abstract

Abstract : An antenna array application with high directivity and low sidelobe level (SLL) is an important technology that can enhance the reliability and validity of a communication system. In recent years, swarm intelligence optimisation algorithms have been widely used in the design of antenna arrays. In this study, a hybrid heuristic swarm intelligence optimisation algorithm called cuckoo search–chicken swarm optimisation (CSCSO) is proposed to optimise the excitation amplitude of a linear antenna array (LAA) and the excitation amplitude and spacing between the array elements of a circular antenna array (CAA). The maximum SLL will be obtained while the mainlobe width is fixed. CSCSO combines cuckoo search (CS) and chicken swarm optimisation (CSO) and thus, it will have the excellent global search capability of CS as well as introduce the hierarchy mechanism of CSO to improve algorithm precision. Chaos theory is utilised to determine the initial solution of the algorithm, while Levy flight weight coefficient is used to improve the convergence rate in CSCSO. Simulation results show that CSCSO has a better performance in terms of solution accuracy and convergence rate in the radiation pattern optimisation of LAA and CAA compared with the standard CSO, CS, and particle swarm optimisation algorithms.