I am trying to find out if an algorithm similar to the Overlap-And-Add method that enables frame-based computation of convolution and cross-correlation exists.
When I say frame-based computation I am referring to having a very large input signal vector, subdividing it into smaller frames, processing the autocorrelation of those frames, and then concatenating all of the frame results plus any extra magic to form the overall auto-correlation result as if I had computed the whole thing at once.
Working through toy examples by hand for auto-correlation I quickly realized the normal Overlap-And-Add method doesn't work due to the correlation "template" changing every frame vs generally being fixed in the cross-correlation and convolution cases.