摘要
提出一种基于模拟退火粒子群算法(SAPSO)的同心圆阵稀疏优化方法,该方法以同心圆阵阵元位置为优化参量,以第一零点波束宽度和峰值旁瓣电平为优化目标,结合了模拟退火算法和粒子群算法的优点,提高了算法的收敛速度,具有摆脱局部最优的能力。仿真结果表明,相比于目前常用的4种优化算法,相同迭代次数下,该方法收敛迭代次数最小,且在约束同心圆阵第一零点波束宽度的同时得到的稀疏同心圆阵具有最低的峰值旁瓣电平。
In this paper, a design method of thinned concentric ring arrays base on Simulated-Annealing- based Particle Swarm Optimization （SAPSO） is proposed. Taking the position of elements as variables, first null beam-width （FNBW） and peak side lobe level as fitness function, the convergence velocity of the method is improved and the local optimum can be effectively escaped combined with the advantages of the simulated annealing algorithm and the particle swarm optimization algorithm. The simulation results dem- onstrate that compared with the existing four popular methods of thinning concentric ring array, the first null beam-width of the obtained thinned array is retainable equal to that of the full array and the peak side lobe level is reduced considerably.
出处
《空军工程大学学报（自然科学版）》
CSCD
北大核心
2015年第6期42-45,共4页
Journal of Air Force Engineering University(Natural Science Edition)
基金
国家自然科学基金资助项目(61172148)
关键词
同心圆阵
模拟退火
粒子群算法
旁瓣电平
concentric ring array
simulated annealing （SA）
particle swarm optimization （PSO）
side lobe level
