A Grating Lobe Suppression Method of Wideband Real Time Delay Pattern Based on Particle Swarm Optimization Algorithm
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No. One Department, Air Force Early Warning Academy,Wuhan 430019, China
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摘要: 針對陣元間距大于信號波長引起陣列方向圖出現(xiàn)柵瓣的問題,該文提出一種基于粒子群優(yōu)化(PSO)算法的寬帶真延時方向圖柵瓣抑制方法。該方法首先定義了基于寬帶真延時的陣列能量方向圖,其次構(gòu)造了以陣列能量方向圖的最高副瓣電平作為適應(yīng)度函數(shù),最后利用粒子群優(yōu)化算法優(yōu)化陣元分布來實現(xiàn)對陣列方向圖柵瓣的進一步抑制。仿真結(jié)果表明:相比于單獨使用粒子群算法和單獨使用寬帶真延時方法,該方法對方向圖柵瓣的抑制性能更加有效,在此基礎(chǔ)上,該文還研究了陣元個數(shù)、平均陣元間距、信號時寬和信號中心頻率等因素對方法抑制柵瓣性能的影響。
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關(guān)鍵詞:
- 粒子群優(yōu)化算法 /
- 寬帶真延時 /
- 能量方向圖 /
- 柵瓣抑制 /
- 適應(yīng)度函數(shù)
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. -
表 1 基于粒子群優(yōu)化算法的寬帶陣列方向圖柵瓣抑制方法每次循環(huán)后更新粒子流程
(1) 如果${\rm{MSL}}{{\rm{L}}_{i,q - 1}} > {\rm{MSLL}}_i^q$, ${\rm{MSL}}{{\rm{L}}_{i,q}} \leftarrow {\rm{MSLL}}_i^q$, ${\textq7j3ldu95}{{\textq7j3ldu95}_{i,q}} \leftarrow {\text{dd}}_i^q$;否則${\rm{MSL}}{{\rm{L}}_{i,q}} \leftarrow {\rm{MSL}}{{\rm{L}}_{i,q - 1}}$, ${\textq7j3ldu95}{{\textq7j3ldu95}_{i,q}} \leftarrow {\textq7j3ldu95}{{\textq7j3ldu95}_{i,q - 1}}$; (2) 如果${\rm{MSL}}{{\rm{L}}_{q - 1}}{\rm{ > MSL}}{{\rm{L}}_{i,q}}$, ${\rm{MSL}}{{\rm{L}}_q} \leftarrow {\rm{MSL}}{{\rm{L}}_{i,q}}$, ${{\text{g}}_q} \leftarrow {\text{dd}}_i^q$;否則${\rm{MSL}}{{\rm{L}}_q} \leftarrow {\rm{MSL}}{{\rm{L}}_{q - 1}}$, ${{\text{g}}_q} \leftarrow {{\text{g}}_{q - 1}}$。 注:表中,${\rm{MSLL}}_i^q$為第i個粒子第q次循環(huán)的適應(yīng)度函數(shù)值,${\rm{MSL}}{{\rm{L}}_{i,q}}$為第i個粒子第q次循環(huán)后的最佳適應(yīng)度函數(shù)值,${\rm{MSL}}{{\rm{L}}_q}$為整個粒子群第q次循環(huán)后的最佳適應(yīng)度函數(shù)值。 下載: 導(dǎo)出CSV
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