I’ve got a FFT magnitude spectrum and I want to create a filter from it that selectively passes periodic noise sources (e.g. sinewave spurs) and zero’s out the frequency bins associated with the random background noise. I understand sharp transitions in the freq domain will create ringing artifacts once this filter is IFFT back to the time domain… and so I’m wondering if there are any rules of thumb how to smooth the transitions in such a filter to avoid such ringing.
For example, if the FFT has 1M frequency bins, and there are five spurs poking out of the background noise floor, I’d like to zero all bins except the peak bin associated with each of the five spurs. The question is how to handle the neighboring spur bins to prevent artifacts in the time domain. For example, should the the bin on each side of a spur bin be set to 50% amplitude? Should two bins on either side of a spur bin be used (the closest one at 50%, and the next closest at 25%, etc.)? Any thoughts greatly appreciated. Thanks!
I like the following method:
I find it creates reasonably smooth frequency domain results, although I’ve never tried it on something as sharp as you’re suggesting. You can probably make a sharper filter by using a Kaiser-Bessel window, but you have to pick the parameters appropriately. By sharper, I’m guessing maybe you can reduce the sidelobes by 6 dB or so.
Here’s some sample Matlab/Octave code. To test the results, I used
freqz(h, 1, length(h)*10);.