基于特征矢量稀疏分解的非圆信号DOA估计

A DOA estimation approach for non-circular signals based on sparse reconstruction via main eigenvectors. Electronic Engineering and Applications

文中提出当信源为非圆信号时,基于特征矢量稀疏分解进行DOA估计;并在稀疏恢复过程中,比较空间范数变化对误差的影响。该方法对协方差矩阵进行了扩展,在利用L曲线方法自适应得到正则化参数的同时,对空间范数应用进行了推广。不仅提高信息利用率,能够处理相干信号源,而且不需要已知信号源数目,性能优于平滑处理过后的NC-MUSIC算法。

This articles addresses the problem of direction-of-arrival（DOA） estimation for non- circular signals via main eigenvectors, and an adaptive regularization parameter at different iteration steps is proposed in sparse reconstruction. This new method increases the availability of information and can handle coherent signal, without priori information about the number of signal sources. The performance of this method is compared with smoothing NC-MUSIC, through numerical studies.