Spatial and spectral parameter estimation of multiple source signals

The authors propose a computationally efficient scheme for estimating the spatial (location) and spectral parameters of multiple-source signals using passive array data. The source signals are modeled as possibly correlated narrowband/wideband Gaussian random processes. The authors also allow sensor-to-sensor noise correlation. The proposed algorithm is optimal in the sense that it converges monotonically to the maximum-likelihood (ML) estimates (or, at least, to a stationary point of the likelihood function) of the unknown spatial and spectral parameters.<>