Time delay estimation with unknown spatially correlated Gaussian noise
The problem of estimating the difference in arrival times of a non-Gaussian signal at two spatially separated sensors is considered. The signal is assumed to be corrupted by spatially correlated Gaussian noises of unknown cross-correlation. The author proposes and analyzes two new classes of methods for time delay estimation based on higher order statistics. The proposed methods are conceptually very similar to the traditional cross-correlation-based techniques in that the proposed criteria peak at a lag value equalizing true delay. Since the proposed methods are based upon higher order cumulant statistics of the data, they result in estimators that remain unbiased in the presence of Gaussian noise. >