A novel DOA estimation approach based on sparse decomposition of eigenvector
Zhong Zi-fa · Journal of Circuits and Systems · 2013
The thesis proposes a novel DOA(direction of arrival) estimation method using sparse decomposition of eigenvector on the basic of the sparse characteristic of space signals.Firstly,the biggest eigenvector of covariance matrix is proved to be the linear combination of all steer vectors.Then the biggest eigenvector of covariance matrix is extracted to build sparse decomposition model for DOA estimation,the effects caused by the noise is largely reduced and the sources number estimation is able to skip by this method.The theoretical analysis and experimental results show this new method has a better performance than the MUSIC algorithm in the aspects of accuracy,resolution and adaptability to coherent signals.