基于蝙蝠算法与信号稀疏分解的DOA估计研究  

DOA Estimating Study Based on Bat Algorithm and Sparse Decomposition of Signal

作　　者：冯舒[1] 于战海[2] 王云汉[3] Feng Shu Yu Zhanhai Wang Yunhan(College of Communication Engineering,Jilin University, Changchun 130022,China College of Energy and Power Engineering,Northeast Dianli University, Changchun 132012,China College of Automation Engineering,Northeast Dianli University, Changchun 132012 ,China)

机构地区：[1]吉林大学通信工程学院,吉林长春130022 [2]东北电力大学能源与动力工程学院,吉林长春132012 [3]东北电力大学自动化工程学院,吉林长春132012

出　　处：《甘肃科学学报》2016年第5期1-4,共4页Journal of Gansu Sciences

基　　金：国家自然科学基金(51075175);吉林省产业技术研究与开发项目(JF2012C013-3)

摘　　要：稀疏分解的DOA估计法具有很高的估计精度,但稀疏分解计算量巨大,需要较长的计算时间。针对这一问题,将蝙蝠算法与信号的稀疏分解算法相结合,应用于信号的DOA估计。利用蝙蝠搜索算法搜索路径优、寻优能力强的优点,可快速寻找到正交匹配追踪过程中每一步分解的最佳原子,从而实现信号快速稀疏分解。仿真结果表明,引入蝙蝠算法后,在有效的估计条件下,加快了计算速度,减少了计算量。DOA estimating method of sparse decomposition has very high estimated accuracy,but calculated amount of sparse decomposition is huge and need longer time.Aiming this problem,the method combining Bat algorithm and sparse decomposition in this text is used to estimate signal DOA.By the Bat algorithm＇s advantage of optimized search path and strong ability to search optimization,we can find decomposed optimizing atom in each step of orthogonal matching pursuit process with short time so that the signal can be conducted sparse decomposition quickly.The simulating result shows that calculating speed is accelerated and calculating amount is reduced under available estimating condition with Bat algorithm.

关 键 词：DOA算法 稀疏分解 蝙蝠算法 正交匹配追踪 

分 类 号：TN911.7[电子电信—通信与信息系统]