A novel DOA estimation based on signal subspace structure of uniform linear array
Lena Chang, Chang-Min Cheng, Ziqiao Tang, Shun‐Hsyung Chang · 2007
In the study, we present a novel directions of arrivals (DOAs) estimation by using signal subspace structure of an uniform linear array. The proposed method resolves the directions by using the eigenanalysis of a square matrix formed by the eigencomponents in the signal subspace of data correlation matrix. Simulation results validate the high resolution capacity and fast convergence rate of the proposed method. In addition, the proposed method has less computation burden than Root-MUSIC.