I am measuring the phase shift between two pseudorandom signals using correlation ifft(A.conjugate()*B) and picking out the maximum). That works very well, but takes a lot of time. I roughly know where the peaks are, and don't need the correlation for other shifts.
Is there an adaptive cross-correllation algorithm that would speed up the process if I am only interested in the positions of maxima, and already roughly know their positions? Analog to the sliding DFT?
Maybe running the cross-correlation on a decimated version of data, finding the peaks, interpolating, and then doing a manual correlation around the max?
I already know within 200 samples where the maxima are. The record length is about 200k samples.