论文标题
用于扫描应用的Metagrations辅助高电位稀疏天线阵列
Metagrating-Assisted High-Directivity Sparse Antenna Arrays For Scanning Applications
论文作者
论文摘要
我们提出了一个分析方案,用于设计巨大增强的稀疏天线阵列。与以前的工作不同,所提出的方法不涉及耗时的成本函数优化,主动阵列上的复杂结构操作或苛刻的计算能力。取而代之的是,它仅需要在平面定期安排下次波长电容电线(元原子)的平面周期排列(META-ATOMS),并通过半分析程序通过半分析程序来保证稀疏构型中的栅格裂片的抑制。相应地,我们扩展了先前的公式,以通过主动阵列元素来激发MG,从而得出了连接被动和活动元件分布和电气性能与散射场的分析关系,最终允许解析详细的设备配置,从而导致最佳定向性。重要的是,考虑到典型的主动阵列应用,进一步开发了半分析合成方案,以充分利用系统中各种自由度,并利用它们在维持单个指令光束的同时,在广泛的极端角度支撑扫描。在模拟中经过验证的最终方法也可以很好地适用于大型有限阵列,它为减轻具有扫描功能的稀疏阵列中的光栅裂片提供了原始路径,从而在不依赖全波优化的情况下产生了完整的印刷电路板兼容设计。
We present an analytical scheme for designing metagrating-enhanced sparse antenna arrays. Unlike previous work, the proposed method does not involve time-consuming cost function optimizations, complex structural manipulations on the active array or demanding computational capabilities. Instead, it merely requires the integration of a passive metagrating (MG) superstrate, a planar periodic arrangement of subwavelength capacitively-loaded wires (meta-atoms), synthesized conveniently via a semianalytical procedure to guarantee suppression of grating lobes in the sparse configuration. Correspondingly, we extend previous formulations to enable excitation of the MG by the active array elements, deriving analytical relations connecting the passive and active element distribution and electrical properties with the scattered fields, eventually allowing resolution of the detailed device configuration leading to optimal directivity. Importantly, considering typical active array applications, the semianalytical synthesis scheme is further developed to take full advantage of the various degrees of freedom in the system, harnessing them to support scanning in a wide range of extreme angles while maintaining a single directive beam. The resultant methodology, verified in simulations to work well also for large finite arrays, offers an original path for mitigating grating lobes in sparse arrays with scanning capabilities, yielding a complete printed-circuit-board compatible design without relying on full-wave optimization.