A High-Resolution Low-Sidelobe Beamforming Method for Sparse Antenna Arrays Based on CS-GA

In this paper, a joint beamforming method based on cuckoo search and genetic algorithm (CS-GA) is proposed for sparse array optimization. The locations and feed signal amplitudes of sparse array elements are optimized using CS-GA, and the radiation pattern of optimized spare arrays have superiorities of low sidelobe and high resolution owning to the global optimization and fast convergence advantages of CS-GA. The comparison result of CS-GA, linear array synthesis, and Chebyshev array synthesis demonstrates the superiority of CS-GA in high resolution and low sidelobe array synthesis applications.