摘要
针对有阵列孔径,阵元数目和最小阵元间距3种约束下的稀布圆形阵列综合问题,该文提出了一种基于修正遗传算法的降维优化方法。为了充分利用阵元布阵的自由度,同时使稀布阵列满足多个设计约束,在阵元排布时将2维平面阵列优化设计降维成1维的稀布直线阵列,计算阵列性能时再还原为平面阵列。该方法改进了现有圆阵综合方法中轨迹圆半径和轨迹圆上阵元数分布优化的不足,实现了全部阵元的联合优化,降低了算法的复杂性,同时保证了阵列的旁瓣性能,仿真结果证明了该方法的有效性。
A dimensionality reduction method based on modified genetic algorithm is presented under the constraints of fixing the aperture, the number of elements and the minimum element spacing. In order to utilize effectively the freedom of array element, the proposed method transforms the positions of two-dimensional concentric rings array optimization design into one-dimensional linear array when sparse array meet multiple optimization constraints, and then restore to the concentric rings array when calculating its performance. The proposed method reduces greatly the computation time and the complexity of the model. Meanwhile, due to the combined optimization of all elements, the optimization design is improved. Simulation results demonstrate the effectiveness of the proposed method.
出处
《电子与信息学报》
EI
CSCD
北大核心
2014年第2期476-481,共6页
Journal of Electronics & Information Technology
基金
国家自然科学基金(U1233103)
中国博士后科学基金(2012M511919)资助课题
关键词
稀布阵列
圆形阵列
旁瓣性能
遗传算法
降维
Sparse array
Concentric rings array
Side lobe level
Genetic algorithms
Dimensionality reduction
