基于蚁群优化算法的非均匀子阵划分技术

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 subarray partitioning technology based on ant colony optimization algorithm

For large-scale array antennas in the airspace anti-interference system, in order to reduce hardware cost and reduce calculation complexity, the entire array is generally divided into several sub-array by sub-array division technology, analog beamforming is used inside the sub-array, and digital adaptive beamforming is used between the sub-arrays; Because there are grating nulls in the beamforming pattern of uniform partition method, a non-uniform subarray partition technology based on ant colony algorithm is proposed. The maximum output signal-to-interference-noise ratio of the array is taken as the fitness function, and the path planning method combining probability calculation with roulette wheel is applied; Combining the initial concentration of pheromone and heuristic information range, a new transformation relationship between fitness function value and pheromone update is designed; Finally, the simulation 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 ratio 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 signal-to-interference-noise ratio, which verifies the effectiveness of the proposed method.