volume | PIER Journals

Abstract

This paper presents a hybrid method that combines the improved sparrow search algorithm (ISSA) and convex programming (CP) to synthesize sparse arrays under multiple design constraints. The proposed method initiates with introducing ISSA, which establishes a sparse array layout while effectively reducing peak sidelobe levels (PSLLs) through optimizing nonuniform element positions. Subsequently, when the position is fixed, the subproblem of minimizing PSLL is transformed into a convex problem with beamwidth constraint, employing CP to determine optimal excitation amplitudes. The PSLL serves as the fitness function in ISSA to simultaneously optimize both element position and excitation amplitude, to achieve PSLL reduction of sparse array. Afterward, some examples of linear and rectangular planar arrays with low sidelobe are simulated and discussed in detail. Numerical experiments show the effectiveness and reliability of ISSA-CP, which can further reduce PSLL while saving array elements. Ultimately, utilizing the numerical simulation results as a foundation, a full-wave simulation is undertaken to verify the practicality of the novel hybrid method.

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Ms. Qi Tang

Professor Bin Wang

Dr. Xue Tian