顾崴.基于稀疏加权重构的互耦阵列方位估计算法[J].电子测量技术,2016,39(12):67-71
基于稀疏加权重构的互耦阵列方位估计算法
Weighted sparse representation method for DOA estimation with unknown mutual coupling
  
DOI:
中文关键词:  方位估计  阵元互耦  稀疏重构  加权  奇异值分解
英文关键词:DOA estimation  mutual coupling  sparse reconstruction  weighted  SVD
基金项目:
作者单位
顾崴 北京理工大学 信息与电子学院北京100081 
AuthorInstitution
Gu Wei School of Information and Electronics, Beijing Institute of Technology, Beijing 100081, China 
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中文摘要:
      为降低阵元互耦对目标方位估计的影响,提高估计精确度,提出了一种基于稀疏信号加权重构的多目标方位估计算法。该算法将空间以1°为间隔,划分为网格。利用空域目标方位的稀疏性,给出了基于Capon谱函数的加权值选取方法。然后,运用稀疏重构方法和奇异值分解方法对信号进行降维处理。最后,通过L1范数约束优化模型进行DOA估计。仿真结果表明,相比于传统算法,所提出的算法具有更高的方位估计精度、更低的均方根误差,能更好地抑制阵元互耦对目标方位估计的影响。
英文摘要:
      In order to reduce the influence of mutual coupling on DOA estimation, this paper proposes a weighted sparse representation method for DOA estimation with unknown mutual coupling. The proposed method divides the space into grids. Each grid is 1° partitioned. We utilize the Capon spectrum to design a weighted weights with unknown mutual coupling and propose to use the SVD of the data matrix to mold the problem with reduced dimensions. At last, we estimate the angle of the signal based on the L1 norm. Simulation results demonstrate that our proposed method can obtain better DOA estimation result and lower RMSE. Compared with traditional methods, the new algorithm can effectively suppress the unknown mutual coupling.
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