A Novel Subspace Coherent Signal Processing Algorithm For High-Resolution DOA Estimation
Xu Dihua, Chen Jianwen, You Wu · 2006
In this paper, a novel subspace coherent signal processing algorithm for high-resolution direction of arrival (DOA) estimation is proposed, which is based on forward-backward averaging and subspace eigendecomposition, the FB-SED algorithm for short. The forward-backward averaging matrix is employed as the preprocessor for the linear arrays, and then the invariance property of noise subspace to power emitters is used to estimate the directions of the coherent sources. The simulation results indicate that the FB-SED algorithm provides higher resolution performance for two closely spaced coherent sources estimation compared to conventional forward backward spatial smoothing MUSIC (FBSS-MUSIC). Finally, it is shown that FB-SED algorithm is more robust than FBSS-MUSIC when there are array errors in the practical linear array