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To do accurate amplitude measurements on an digital radar receiver, I am searching for the best method to get the amplitude out of a FFT. The signal is windowed using a Blackman window.

So far I'm only looking for the best way to reduce scalloping loss. I'm already in the frequency domain and want to find the real peak of the FFT spectrum. I already tried parabolic interpolation, but this gives errors if the signal is near the noise level.

What is the best way to reduce scalloping loss errors without using a flattop window?

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  • $\begingroup$ Maybe modern spectral estimation method such as MUSIC is better than FFT. $\endgroup$
    – ZR Han
    Aug 20 '21 at 9:51
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You can interpolate using the transform of your chosen window function as the interpolation kernel (similar to Sinc reconstruction), and then use successive approximation to find the peak of the interpolated spectrum.

Pre-constructing a polyphase table using an extremely oversampled transform of your chosen window might or might not assist in this computation.

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  • $\begingroup$ Thanks, can you give a example or a reference where I can get more information about this interpolation principle? $\endgroup$
    – Tim Lipper
    Mar 22 '21 at 8:10
  • $\begingroup$ ccrma.stanford.edu/~jos/st/Reconstruction_Samples_The_Math.html $\endgroup$
    – hotpaw2
    Mar 22 '21 at 15:16
  • $\begingroup$ The following document from Bruel and Kjaer here discusses Picket Fence correction - see App F. You have to first interpolate to find the frequency and then interpolate the amplitude for that frequency. As your sinusoid gets closer to the noise floor you'll get more errors. $\endgroup$
    – David
    Aug 20 '21 at 14:55

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