摘要
提出了一种基于迭代算法的可扫描稀疏阵综合方法。该方法包含凸优化算法,将控制主瓣宽度的非凸优化问题转化成凸约束问题,并结合压缩感知理论,将构建理想辐射性能方向图的具有周期结构的稀疏阵列综合问题转化为迭代加权L1范数最小化的稀疏重构问题,收敛过程中将本次迭代获得的激励权值闭式解作为下次迭代的初值,由完成迭代过程后获得的激励向量中的非零解来确定激励权值以及可用阵元位置。本文实现的扫描最大化稀疏阵列低副瓣设计与竞争算法综合结果相比,在方向图主瓣不展宽的情况下需要的阵列单元总数明显减少。
A synthesis method of steerable sparse and arrays is proposed based on the iterative algorithm.The method includes the convex optimization algorithm,which converts the non-convex optimization problem of controlling the width of the main lobe into a convex constraint problem,and combines the theory of compressed sensing to convert the sparse array synthesis problem with periodic structure that constructs an ideal radiation performance pattern into the sparse reconstruction problem with an iterative weighted L1 minimum norm.The closed-form solution of the excitation weight obtained in this iteration is used as the initial value of the next iteration during the convergence,and the excitation weight and the available array element positions are determined by the non-zero solution in the excitation vector obtained after the iteration is completed.Compared with the comprehensive results of competitive algorithms,the design of maximally steerable sparse array low sidelobe can be achieved,indicating that the total number of array elements required is significantly reduced when the main lobe of the pattern is not widened.
作者
孔玥
邱明华
黄晟
祁峥东
陈浩
KONG Yue;QIU Ming-hua;HUANG Sheng;QI Zheng-dong;CHEN Hao(No. 8 Research Academy of CSSC, Nanjing 211153;School of Physics and Electronic Information, Anhui Normal University, Wuhu 241002, China)
出处
《雷达与对抗》
2020年第3期33-37,共5页
Radar & ECM
基金
安徽省自然科学基金(1908085QF279)。
关键词
方向图综合
凸优化
压缩感知
扫描天线
稀疏天线阵列
pattern synthesis
convex optimization
compressed sensing
scanning antenna
sparse antenna array
