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I am using matched filters using GNU Radio to extract from noise a CW Morse signal. The filter actually performs pretty well in various SNR environments. My problem is that the threshold upon I decide for a presence or absence of a CW transmission vary with different SNR/CW frequency/WPM/incoming signal amplitude setups.

Conventional normalization methods, (eg dividing with the max value) are not applicable since the program runs continuously and the max value is not known a priori. I believe that a moving normalization scheme should deal with this problem. In the past, for preamble detection I have used the moving normalized autocorrelation method that is depicted below (C and P are moving sums). I tried to adapt this approach in my case but with no luck. autocorrelation normalization

My question is, if there is a method to normalize either the output signal power of the matched filter or the input signal itself, so I can rely on a one predefined decision threshold for CW signal presence/absence.

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  • $\begingroup$ I would suggest looking into GnuRadio's AGC block. $\endgroup$ – MBaz Feb 19 '16 at 22:43
  • $\begingroup$ @MBaz thanks. I thought about the solution of AGC. Hoverer the parameters of the AGC is a process of try-and-error and I would like to know if someone suggests a better method. $\endgroup$ – Manos Feb 20 '16 at 21:38

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