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A novel class of methods that estimate the difference in arrival time between signals corrupted by spatially correlated Gaussian noise sources of unknown cross correlation is presented. The methods are based on the idea of comparing the similarities between the two sensor measurements in higher-order spectrum domains (bispectrum) rather than in the cross-correlation domain. It is demonstrated that estimation techniques based on higher-order cumulants suppress the effect of correlated Gaussian noise sources and therefore exhibit improved performance over generalized cross-correlation methods. Results are reported for different types of signals, lengths of data records, and signal-to-noise ratios.>
Nikias et al. (1988) studied this question.