A Grating Lobe Suppression Method of Wideband Real Time Delay Pattern Based on Particle Swarm Optimization Algorithm
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摘要: 针对阵元间距大于信号波长引起阵列方向图出现栅瓣的问题，该文提出一种基于粒子群优化(PSO)算法的宽带真延时方向图栅瓣抑制方法。该方法首先定义了基于宽带真延时的阵列能量方向图，其次构造了以阵列能量方向图的最高副瓣电平作为适应度函数，最后利用粒子群优化算法优化阵元分布来实现对阵列方向图栅瓣的进一步抑制。仿真结果表明：相比于单独使用粒子群算法和单独使用宽带真延时方法，该方法对方向图栅瓣的抑制性能更加有效，在此基础上，该文还研究了阵元个数、平均阵元间距、信号时宽和信号中心频率等因素对方法抑制栅瓣性能的影响。Abstract: A grating lobe suppression method of wideband real time delay pattern based on Particle Swarm Optimization(PSO) algorithm is proposed to solve the problem of grating lobe arise from inter-element is larger than wavelength. Firstly, the array energy pattern based on wideband real time delay is defined. Then, a fitness function is constructed with maximum sidelobe level of the array energy pattern. Finally, the grating lobe is further suppressed by optimizing the elements position distribution using Particle Swarm Optimization (PSO) algorithm. The simulation results show that the proposed grating lobes suppression method is more effective than individually using the particle swarm optimization method or the wideband real time delay method. Furthermore, the influence of the element space, the element number, the time width and the center frequency of signal on the performance of grating lobe suppression are studied.
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表 1 基于粒子群优化算法的宽带阵列方向图栅瓣抑制方法每次循环后更新粒子流程
(1) 如果${\rm{MSL}}{{\rm{L}}_{i,q - 1}} > {\rm{MSLL}}_i^q$, ${\rm{MSL}}{{\rm{L}}_{i,q}} \leftarrow {\rm{MSLL}}_i^q$, ${\text{d}}{{\text{d}}_{i,q}} \leftarrow {\text{dd}}_i^q$；否则${\rm{MSL}}{{\rm{L}}_{i,q}} \leftarrow {\rm{MSL}}{{\rm{L}}_{i,q - 1}}$, ${\text{d}}{{\text{d}}_{i,q}} \leftarrow {\text{d}}{{\text{d}}_{i,q - 1}}$； (2) 如果${\rm{MSL}}{{\rm{L}}_{q - 1}}{\rm{ > MSL}}{{\rm{L}}_{i,q}}$, ${\rm{MSL}}{{\rm{L}}_q} \leftarrow {\rm{MSL}}{{\rm{L}}_{i,q}}$, ${{\text{g}}_q} \leftarrow {\text{dd}}_i^q$；否则${\rm{MSL}}{{\rm{L}}_q} \leftarrow {\rm{MSL}}{{\rm{L}}_{q - 1}}$, ${{\text{g}}_q} \leftarrow {{\text{g}}_{q - 1}}$。 注：表中，${\rm{MSLL}}_i^q$为第i个粒子第q次循环的适应度函数值，${\rm{MSL}}{{\rm{L}}_{i,q}}$为第i个粒子第q次循环后的最佳适应度函数值，${\rm{MSL}}{{\rm{L}}_q}$为整个粒子群第q次循环后的最佳适应度函数值。 
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