Sparse Bayesian Learning for DOA Estimation of Correlated Sources
Christoph F. Mecklenbriiuker, Peter Gerstoft, Geert J. T. Leus · 2018
Direction of arrival (DOA) estimation from array observations in a noisy environment is discussed. The source amplitudes are assumed to be correlated zero-mean complex Gaussian distributed with unknown covariance matrix. The DOAs and covariance parameters of plane waves are estimated from multi-snapshot sensor array data using sparse Bayesian learning (SBL). The performance of SBL is evaluated in terms of the fidelity of the reconstructed coherency matrix of the estimated plane waves.