If I have two sensor measuring the same signal but from two different locations from the source, and I get two different readings of the signal, each with slightly different noise.
Is there a way to use the cross correlation of the signals to get a third signal which represents the components of the signal which are common across both measurements?
The reason I ask is that I have tried to do this, and I can get the cross correlation signal, but I can't figure out how to use this to get back to something that looks like the original signal, see below 
i.e. How can I get something which looks like a mix of the green and blue signals from the red one?