基于改进人工蜂群算法的MIMO雷达稀疏阵列优化

doi:10.3969/j.issn.1001-506X.2018.05.10

系统工程与电子技术 ›› 2018, Vol. 40 ›› Issue (5): 1026-1030.doi: 10.3969/j.issn.1001-506X.2018.05.10

基于改进人工蜂群算法的MIMO雷达稀疏阵列优化

庞育才, 刘松

重庆邮电大学国防信息工程技术研究院, 重庆 400065

出版日期:2018-04-28 发布日期:2018-04-24

Optimization of MIMO radar sparse array based on modified artificial bee colony

PANG Yucai, LIU Song

National Defense Information Engineering Technology Institute, Chongqing University of Post and Telecommunications, Chongqing 400065, China

Online:2018-04-28 Published:2018-04-24

摘要/Abstract

摘要：

为了提高多输入多输出(multiple input multiple output, MIMO)雷达稀疏阵列性能,提出了一种基于云模型的改进离散人工蜂群算法对MIMO雷达稀疏阵列进行优化。该算法首先对人工蜂群算法进行改进,用云模型替代轮盘赌作为新的选择模型来选择较优蜜源。云模型的随机性和稳定倾向性,能够维持种群的多样性,从而克服了人工蜂群算法易陷入局部最优的问题。为了保证搜索过程中阵元数量保持不变,加入了新的限制条件。仿真实验结果表明,该算法具有良好的性能,能够在保持主瓣宽度不变的情况下,得到更低的旁瓣水平。

Abstract:

To improve the performance of multiple input multiple output (MIMO) radar sparse arrays, a modified discrete artificial bee colony (ABC) algorithm based on the cloud model is proposed for optimizing MIMO radar sparse arrays. First, ABC is modified by using the cloud model as a new selection scheme rather than roulette for a better nectar source. Due to randomness and stable tendency of the cloud model, the diversity of the population is maintained, and thus the disadvantage of ABC can be avoided, which results in a local optimum easily. Then, a new restriction is added to ensure a fixed number of array elements in the search process. Simulation results verify the effectiveness of the proposed method. Lower sidelobes are obtained while the width of the mainlobe is kept constant.

庞育才, 刘松. 基于改进人工蜂群算法的MIMO雷达稀疏阵列优化[J]. 系统工程与电子技术, 2018, 40(5): 1026-1030.

PANG Yucai, LIU Song. Optimization of MIMO radar sparse array based on modified artificial bee colony[J]. Systems Engineering and Electronics, 2018, 40(5): 1026-1030.

基于改进人工蜂群算法的MIMO雷达稀疏阵列优化

Optimization of MIMO radar sparse array based on modified artificial bee colony

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