| 幅值比约束下稀布阵的旁瓣抑制混合算法 |
| |
| 引用本文： | 孙洁,李海林,曹爱华,金灿,周建江.幅值比约束下稀布阵的旁瓣抑制混合算法[J].现代雷达,2018,40(7):57-60. |
| |
| 作者姓名： | 孙洁 李海林 曹爱华 金灿 周建江 |
| |
| 作者单位： | 南京航空航天大学电子信息工程学院,南京211100,南京航空航天大学电子信息工程学院,南京211100,南京航空航天大学电子信息工程学院,南京211100,南京航空航天大学电子信息工程学院,南京211100,南京航空航天大学电子信息工程学院,南京211100 |
| |
| 基金项目： | 国家自然科学基金资助项目(61671239);南京航空航天大学研究生创新基地(实验室)开放基金资助项目(ktjj20160404);中央高校基本科研业务费专项资金资助 |
| |
| 摘 要： | 针对非均匀稀布圆环阵的旁瓣抑制问题提出了一种基于粒子群算法和二阶锥规划算法的混合算法。该混合算法结合两种算法的优势,将粒子群算法作为全局搜索器进行阵元位置的优化,二阶锥规划算法作为局部搜索器进行阵元权值的优化,能够获取较低的峰值旁瓣电平。该算法同时引入相邻阵元最小间距的约束,优化了算法的搜索空间,提高了寻优效率。最后,考虑到阵列天线系统的可实现性,给出了动态幅值比约束下的混合算法。与粒子群算法和参考文献方法的对比实验结果表明:本文算法可进一步降低稀布圆环阵的旁瓣电平,仿真数据验证了算法的有效性和天线系统的可实现性。
|
| 关 键 词： | 稀布阵列 旁瓣电平 粒子群 二阶锥规划 动态幅值比 |
A Hybrid SLL Suppression Algorithm for Sparse Array Under the Constraint of Amplitude Range Ration |
| |
| SUN Jie,LI Hailin,CAO Aihu,JIN Can and ZHOU Jianjiang.A Hybrid SLL Suppression Algorithm for Sparse Array Under the Constraint of Amplitude Range Ration[J].Modern Radar,2018,40(7):57-60. |
| |
| Authors: | SUN Jie LI Hailin CAO Aihu JIN Can and ZHOU Jianjiang |
| |
| Affiliation: | College of Electronic Information and Engineering, Nanjing University of Aeronautics and Astronautics,Nanjing 211100, China,College of Electronic Information and Engineering, Nanjing University of Aeronautics and Astronautics,Nanjing 211100, China,College of Electronic Information and Engineering, Nanjing University of Aeronautics and Astronautics,Nanjing 211100, China,College of Electronic Information and Engineering, Nanjing University of Aeronautics and Astronautics,Nanjing 211100, China and College of Electronic Information and Engineering, Nanjing University of Aeronautics and Astronautics,Nanjing 211100, China |
| |
| Abstract: | A hybrid algorithm, based on particle swarm optimization (PSO) algorithm and second-order cone programming (SOCP) algorithm is proposed to suppress the side-lobe level(SLL) of the non-uniform sparse circular array. It takes full advantages of each single algorithm to obtain a low peak side-lobe level, in which PSO is used as the global searcher to optimize the positions of array elements and SOCP is used as the local searcher to obtain the optimal weight excitation. Meanwhile, the searching space range is reduced and the efficiency is improved by the introduction of the constraint of the minimize distance between two adjacent array elements. Finally, an effective method is proposed to optimize the amplitude dynamic range ratio, making the system achievable in practical application. The comparison experiment results among PSO, methods of reference and our algorithm show that our algorithm can further reduce the side-lobe level, which indicates that proposed algorithm is competitive and easy to realize. |
| |
| Keywords: | sparse array side-lobe level particle swarm optimization second-order cone programming amplitude dynamic range ratio |
|
| 点击此处可从《现代雷达》浏览原始摘要信息 |
|
点击此处可从《现代雷达》下载全文 |
|
