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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 enter image description here

i.e. How can I get something which looks like a mix of the green and blue signals from the red one?

Stephen Jackson
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  • that's exactly what matched filters do! – Marcus Müller Jun 24 '19 at 08:37
  • when you say same signal, do they have the same bandwidth? is there a known delay between the two? –  Jun 24 '19 at 12:07
  • They have the same bandwidth, and there could be a possible very slight delay just because one might be a little bit further away from the source than the other, but it's not known – Stephen Jackson Jun 24 '19 at 12:27
  • have you tried adding them? –  Jun 24 '19 at 12:33
  • Sorry, I'm not exactly sure what you're suggesting, do you mean I try to average each point? I have not tried this but I will certainly give it a go – Stephen Jackson Jun 24 '19 at 13:16
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    How about considering an approach such as this one, using your two signals to determine the related cross-channel and then once aligned combining them to maximize your SNR (+3 dB): https://dsp.stackexchange.com/questions/31318/compensating-loudspeaker-frequency-response-in-an-audio-signal/31326#31326 – Dan Boschen Jun 26 '19 at 12:07

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