基于均匀圆阵的矢量重构解相干算法

为解决基于均匀线阵矢量重构法不能直接用于均匀圆阵这一问题,提出一种模式空间矢量重构算法.提取模式变换后最大广义特征值对应的特征矢量,并对修正的信号特征矢量采用前后矢量重构方式构造数据矩阵实现解相干.在变换前提取最大特征值对应的信号特征矢量,充分去除噪声,且无需变换后广义特征分解计算,算法复杂度显著降低.理论分析和仿真结果验证了该算法的有效性.

DOA estimation of coherent signals based on vector reconstruction with uniform circular arrays

To solve the problem that vector reconstruction method with uniform linear arrays cannot be used directly in uniform circular arrays, an efficient vector reconstruction algorithm based on space mode for DOA estimation is proposed. The eigenvector corresponding to the largest generalized eigenvalue of the covariance matrix is corrected to acquire signal eigenvectors after mode excitation. The receiving data matrix is constructed by the forward-backward vector reconstruction to estimate DOA of coherent signals. Optimization algorithm is presented to acquire the largest signal subspace eigenvector by performing eigen-decomposition before mode excitation, which eliminates the noise fully and avoids the generalized eigen-decomposition on the virtual linear arrays, and the computation complexity is reduced obviously. The theoretical analysis and numerical examples are provided to demonstrate effectiveness of the proposed approach.