基于蝙蝠算法与信号稀疏分解的DOA估计研究

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 Study Based on Bat Algorithm and Sparse Decomposition of Signal

DOA estimating method of sparse decomposition has very high estimated accuracy,but calculat-ed amount of sparse decomposition is huge and need longer time.Aiming this problem,the method combi-ning Bat algorithm and sparse decomposition in this text is used to estimate signal DOA.By the Bat algo-rithm's advantage of optimized search path and strong ability to search optimization,we can find decom-posed optimizing atom in each step of orthogonal matching pursuit process with short time so that the sig-nal can be conducted sparse decomposition quickly.The simulating result shows that calculating speed is ac-celerated and calculating amount is reduced under available estimating condition with Bat algorithm.