High‐resolution DOA estimation for closely spaced correlated signals using unitary sparse Bayesian learning
Wenying Lei, Baixiao Chen · Electronics Letters · 2015
A novel method is proposed to effectively solve the challenging problem of direction‐of‐arrival (DOA) estimation for closely spaced correlated signals. A centro‐Hermitian extended matrix is exploited to double the number of data samples, and then is transformed into a real‐valued data matrix. An improved sparse Bayesian learning scheme is utilised to estimate DOAs by recovering the real‐valued jointly row‐sparse solution matrix with a reduced computational burden. The proposed method not only provides increased estimation accuracy but also has improved angular separation performance. Simulation results validate the effectiveness of the proposed method.