摘要
为了解决多输入多输出(Multiple-input multiple-output,MIMO)雷达因稀疏布阵导致旁瓣过高的问题,该文主要研究将差集理论用于MIMO雷达阵列稀疏优化。讨论了两种基于差集理论的阵列设计方法,分别适用于对布阵算法运算量敏感与否两种情况。对于运算量敏感的场合,提出一种采用差集理论进行MIMO雷达快速布阵的方法,所得阵列方向图的峰值旁瓣比优于常用的随机阵列;对于运算量不敏感的场合,采用一种将差集理论和遗传算法相结合的优化方法,可用较快的收敛速度获得比传统遗传算法更优的结果。最后通过仿真验证了所提方法的有效性。
To solve the problem that the sidelobe of multiple-input multiple-output(MIMO)radar sparse arrays is too high,this paper presents an approach for thinning MIMO radar arrays using the difference set theory.Array design methods are studied both for applications to computation-sensitive to array algorithm or not.When the applications are sensitive to computation complexity,a fast array element locating algorithm,based on the difference set theory,is given.It can yield results that have lower peak sidelobe levels than random arrays which are commonly used.In the applications insensitive to computation complexity,a method which combines the difference set theory with the genetic algorithm is offered.Better performance and faster convergence can be achieved using the method than using a conventional genetic algorithm.Finally,the simulations are performed to verify the efficience of the proposed methods.
出处
《南京理工大学学报》
EI
CAS
CSCD
北大核心
2013年第4期463-470,共8页
Journal of Nanjing University of Science and Technology
基金
部预研基金(9140A07010311BQ02)
教育部博士点基金(20113219110018)
南京理工大学研究基金(2010ZDJH05
2011ZDJH13)
江苏省普通高校研究生科研创新计划资助项目(CXZZ11_0252)
关键词
多输入多输出雷达
差集理论
稀疏阵列
遗传算法
阵列优化
multiple-input multiple-output radar
difference set theory
sparse arrays
genetic algorithm
array optimization
