Array processing in correlated noise fields based on joint eigen-decomposition of spatial-temporal correlation matrices

Direction of arrival (DOA) estimation techniques require knowledge of the sensor-to-sensor correlation of the noise which constitutes a significant drawback. In the case of temporally correlated signals, it is possible to estimate the signal parameters without any assumptions made on the spatial covariance matrix of the noise. In this paper we present a new method for the estimation of the signal subspace and noise subspace. The proposed approach is based on the joint eigendecomposition (JED) of a combined set of spatio-temporal correlation matrices. Once the signal and the noise subspaces are estimated, any subspace based approach can be applied for DOA estimation. Performance comparisons of the proposed approach with two existing techniques are provided.