Generalized Cross Correlation
EDIT  The OP mentions below Deve's answer that this was not the "Generalized Cross Correlation" algorithm referred to.  The real one seems to be this one:



This paper seems to give equations about how to implement it in the time domain.

The equation they give is basically what Deve reports below. The key point they make is that the "input" to the cross-correlation is not the bare signals, but the residuals of an LMS algorithm applied to the bare signals.  

This as the effect of pre-whitening the input signals.





The method seems to be from this paper:

Azaria, M.; Hertz, D., "Time delay estimation by generalized cross correlation methods," Acoustics, Speech and Signal Processing, IEEE Transactions on , vol.32, no.2, pp.280,285, Apr 1984

doi: 10.1109/TASSP.1984.1164314

Abstract: The problem of estimating time delay by cross correlation methods is reexamined for the whole class of stationary signals. Expressions are derived for the estimation mean square error (MSE) by the cross correlation method, and are shown to be identical to previously published results for Gaussian signals. The generalized cross correlation method is also analyzed, and the optimal weight function for this method is derived. It is shown to be identical to that derived for Gaussian signals by the maximum likelihood method. For the cross correlation method a simplified MSE expression is derived, which is to be used instead of a previously published result.

keywords: {Autocorrelation;Bandwidth;Correlation;Delay effects;Delay estimation;Error analysis;Estimation error;Maximum likelihood estimation;Mean square error methods;Signal to noise ratio}

From which the key formula appears to be:



where