volume | PIER Journals

Abstract

In modern wireless systems, such as radar, satellite communication and 5G communication, planar antenna arrays can achieve high-performance radiation characteristics. The synthesis of these arrays that can produce patterns with low peak sidelobe levels (PSLL) is critical for improving the performance of the antenna system. However, the synthesis of large-scale planar arrays presents a complex nonlinear optimization challenge because of the vast number of variables which leads to high design complexity. To address these issues, an improved hybrid optimization method which is called ICOK-Hybrid Algorithm is proposed. The hybrid algorithm integrates Invasive Weed Optimization (IWO), Convex Optimization (CO) and K-means clustering. The convex optimization is used to efficiently optimize the excitation amplitudes and phases while the IWO algorithm is used to refine the positions of the array elements. Furthermore, an innovative subarray partitioning strategy based on an improved K-means algorithm was introduced to group elements with similar excitations which significantly reduces the design complexity and hardware costs. Numerical results demonstrate that the proposed algorithm achieves a significantly lower PSLL compared with the results obtained by other methods. The practical feasibility and reliability of the proposed approach are further verified by full-wave electromagnetic simulation software CST.

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Dr. Chenxin Ren

Dr. Hua Guo

Dr. Yang Xiao

Dr. Peng Song

Dr. Lijian Zhang