首页|基于蚁群优化算法的非均匀子阵划分技术

基于蚁群优化算法的非均匀子阵划分技术

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对于大型阵列天线应用于空域抗干扰系统中,为了降低硬件成本和减少计算复杂度,一般通过子阵划分技术将整个阵列划分为若干子阵,子阵内部采用模拟波束形成,子阵间采用数字自适应波束形成;由于均匀划分方法的波束形成方向图中存在栅零点,提出一种基于蚁群算法的非均匀子阵划分技术,将阵列最大输出信干噪比作为适应度函数,应用了概率计算与轮盘赌相结合的路径规划方法;结合信息素初始浓度和启发式信息范围,设计了新的适应度函数值与信息素更新的转换关系;最后对所提算法进行仿真,结果表明在不同规模、不同输入干噪比、不同期望信号扫描角度下,所提算法在输出信干噪比上优于均匀划分方法,且没有栅零点产生,与全阵元的自适应波束形成方向图、输出信干噪比相近,验证了该方法的有效性。
Non Uniform Sub-array Partitioning Technology Based on Ant Colony Optimization Algorithm
For large-scale array antennas in airspace anti-interference systems,in order to reduce hardware cost and reduce calcu-lation complexity,an entire array is generally divided into several sub-array by sub-array division technology,the analog beamforming is generated in the sub-array,and the digital adaptive beamforming between sub-arrays;Because there are grating nulls in the beam-forming pattern of the uniform partition method,a non-uniform sub-array partition technology based on ant colony algorithm is pro-posed.The maximum output signal-to-interference-noise ratio of the array is taken as the fitness function,which applies the path planning method combining the probability calculation with roulette wheel;By combining the initial concentration of pheromone and heuristic information range,a new transformation relationship between fitness function value and pheromone update is designed;Fi-nally,The proposed algorithm is simulated,the results show that the proposed algorithm is superior to the uniform partition method in the output signal-to-noise ratio at different scales,different input interference-to-noise ratios and different desired signal scanning angles,and there is no grid zero,which is similar to the adaptive beamforming pattern of the whole array element and the output sig-nal-to-interference-noise ratio,and it verifies the effectiveness of the proposed method.

sub-array partitionant colony algorithmadaptive beamformingUAV measurement and controlIntelligent algo-rithm

米泽辉、郭肃丽、秦固平、王明杰

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中国电子科技集团公司第54研究所,石家庄 050081

中国人民解放军31585部队,北京 100144

子阵划分 蚁群算法 自适应波束形成 无人机测控 智能算法

2024

计算机测量与控制
中国计算机自动测量与控制技术协会

计算机测量与控制

CSTPCD
影响因子:0.546
ISSN:1671-4598
年,卷(期):2024.32(1)
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