Large‐scale antenna arrays (LSAAs) are used to achieve satisfactory performance in 5G communications and radar systems. However, sidelobe suppression and nulls control of LSAAs are high‐dimensional nonlinear optimization problems owing to the large number of antenna elements. In this study, we formulate an optimization problem for joint sidelobe suppression and nulls control of large‐scale linear antenna arrays and propose particle swarm optimization with global search and population mutation (PSOGP) to solve this problem. PSOGP introduces global search and population mutation operators into conventional particle swarm optimization to improve performance in terms of convergence rate and accuracy in large solution spaces. Simulation results demonstrate that compared with other methods, the proposed PSOGP has better overall performance in joint sidelobe suppression and nulls control.

中文翻译：

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全局搜索和种群变异的粒子群算法联合抑制大型线性天线阵列的旁瓣和零点控制

大规模天线阵列（LSAA）用于在5G通信和雷达系统中获得令人满意的性能。然而，由于天线元件数量众多，LSAA的旁瓣抑制和零位控制是高维非线性优化问题。在这项研究中，我们为大型线性天线阵列的联合旁瓣抑制和零位控制制定了一个优化问题，并提出了具有全局搜索和种群变异（PSOGP）的粒子群优化算法来解决此问题。PSOGP在常规粒子群优化中引入了全局搜索和种群突变算子，以提高大解空间中的收敛速度和准确性，从而提高了性能。仿真结果表明，与其他方法相比，