基于自适应遗传算法的稀布阵天线优化

稀布阵能够以较少的天线单元,通过稀布的方式和先进的处理算法获得与传统等间距阵相当的孔径效能,降低了系统的硬件成本,具有灵活布置的优点、重要的研究意义和应用价值。稀布阵与同口径满布阵相比副瓣电平较高。文中提出了一种基于自适应遗传算法的稀布阵列综合优化方法。该算法采用实值编码方式,引入自适应遗传算子,有效提高了优化效率,避免陷入个体早熟及局部收敛,得到了更低的副瓣电平。给出了具体实现步骤以及仿真实例,结果表明,采用自适应遗传算法,得到了更低的稀布阵天线副瓣电平。

Optimization of Sparse Array Based on Adaptive Genetic Algorithm

Sparse array plays an important role in the design of real radar system because of its low cost and system complexity. However, it has higher side-lobe level. In order to obtain lower side lobe level, an optimization method of sparse array is proposed based on adaptive genetic algorithm(AGA). The genetic algorithm''s performance will be improved by using a real-valued coding and adaptive processing of genetic operator. The results of process and simulation by computer show that lower side-lobe lever can be achieved with this method.