On a fast digital method of estimating the autocorrelation of a gaussian stationary process

The zero-mean stationary Gaussian processes have the property that if they are input into an instantaneous nonlinear device, the cross correlation of input and output is proportional to the auto-correlation of the input. This suggests an estimation procedure for the autocorrelation function based mainly on additions, which is a modified type of the PCC (polarity coincidence correlator). The object of this paper is to compute the bias and the variance of such an estimator and to discuss some fundamental properties. As a reference, some examples are provided which compare the behavior of the modified PPC estimator to the classical one based on products and additions.