Resolving uncorrelated and correlated sources by linear prediction

The resolution and the estimation error are investigated for two linear prediction (LP) algorithms for bearing estimation with uniform linear array of sensors, in the presence of incoherent and coherent sources: the Burg algorithm (BA) and the generalized Burg algorithm (GBA). The superresolution is easily achieved with both algorithms when the sources are incoherent. For coherent sources, however, the BA estimate is somewhat more sensitive to the magnitude and the phase of the intersignal correlation than the GBA, thereby resulting in the increased error in the bearing estimates.