I've just started studying methods used to detect and then filter out/remove cyclic noise from known signals.
I have a signal of 256 samples which repeats itself. I take this signal, attenuate it and add noise at a specific band (frequency band), for example 50 Hz Sine Wave. In the simplest case this is none varying. However in the future it will vary slowly over time. What I would like to do is find the power level of the additive cyclic noise (, which should be the difference between the two signals) and where in the frequency spectrum this noise exists. Using this information, I would hope to use weighting to recover the original signal. *Steps* 1 I take the original and modified signal and rescale the modified signal to match the original. At the moment I use a very naive approach which is to take the absolute sum of the 256 samples for both signals and from this calculate a simple scale factor. I think this should be OK where I have narrow band noise, but it may fail badly in other cases where the noise levels are high. 2 Next I take the FFT of the two signals (256 samples). 3 Calculate the noise Using the difference between the FFTs, I then calculate the noise power. *Two questions?* 1 The rescaling method is very basic, using absolute accumulated sums. Does GNU radio have any blocks, which could perform this auto-scaling more effectively? 2 Using the basic difference between the FFT's, such as the absolute magnitude difference, should provide a starting point for calculating the noise power. Again is this naive? -- View this message in context: http://gnuradio.4.n7.nabble.com/Calculating-additive-noise-power-for-known-signal-tp61281.html Sent from the GnuRadio mailing list archive at Nabble.com. _______________________________________________ Discuss-gnuradio mailing list [email protected] https://lists.gnu.org/mailman/listinfo/discuss-gnuradio
