Timeline for What's the ideal FFT window for measuring a group of signals of differing amplitudes but close in frequency?
Current License: CC BY-SA 4.0
12 events
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| Jan 14, 2021 at 6:22 | comment | added | OverLordGoldDragon | This answer inspired the default STFT window for ssqueezepy; I've confirmed slight edge of DPSS over Gaussian in time-frequency resolution, and notably narrower main-lobe width. | |
| Dec 13, 2020 at 19:38 | comment | added | Dan Boschen | @BenS. Thanks I understand. I updated my answer to remove the first paragraph. I do believe the rest is very applicable to your application and that a Kaiser window will out-perform the Blackman window (as well as a Gaussian window-- which is used in most spectrum analyzers which is very similar to what you are trying to achieve- for the reasons I gave. | |
| Dec 13, 2020 at 19:36 | history | edited | Dan Boschen | CC BY-SA 4.0 |
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| Dec 13, 2020 at 18:52 | comment | added | Ben S. | All good information, but unfortunately not applicable. I understand there will always be some confusion when OPs like me naively toss around terms like "frequency" when discussing lasers, but I've edited my question to better reflect that it's the CHOPPING frequency I control, and that the laser wavelengths are all different, and known. | |
| Dec 13, 2020 at 13:01 | history | edited | Dan Boschen | CC BY-SA 4.0 |
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| Dec 12, 2020 at 23:13 | comment | added | Dan Boschen | I would need to see the detailed method to see any similarities if they exist. Here he is sampling at a constant rate for 2 seconds with signals 4 seconds apart; his signals themselves may not have the spectral purity to distinguish but if they do then a Kaiser windowed FFT (with beta = 8) would provide about 80 dB dynamic range for that duration and spacing. | |
| Dec 12, 2020 at 20:55 | comment | added | Mark | I'd be happy o see such equivalence. Do you have a link? Yet I was talking about methods form the Compressive Sensing world. | |
| Dec 12, 2020 at 20:53 | comment | added | Dan Boschen | What other method? It’s possible the other method is equivalent to windowing with an FFT (which is identical to heterodyne approaches when you look at the underlying structure of the DFT) in the end the ability to discern closely spaced frequencies in noise is limited by the length of the captured sequence (hence time bandwidth parameters are of interest for any competing approaches) | |
| Dec 12, 2020 at 20:51 | comment | added | Mark | Usually in this scenario it is better not to use windows at all and go to other method which will be able to discern the different frequencies. | |
| Dec 12, 2020 at 20:49 | comment | added | Dan Boschen | @Mark for the choices I mentioned you can trade dynamic range with main lobe width so they should outperform any other windows for this application given the minimum time bandwidth product (they would give you the best selectivity all other things equal) | |
| Dec 12, 2020 at 20:47 | comment | added | Mark | I think the optimal window will depend on the Dynamic Range of data in the question. Though the choices you mentioned are very good in the case no such knowledge exist. | |
| Dec 12, 2020 at 1:54 | history | answered | Dan Boschen | CC BY-SA 4.0 |
