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I am currently operating in vhf band AND trying to detect frequencies using Fast Fourier transform thresholding method. While detection of multiple frequencies , i received spurs(May not appropriate word) in addition with original frequencies, Such as in case of f1,f2 that are incoming frequencies i also receive their sum f1+f2 and difference f1-f2.

i am trying to eliminate these using thresholding method but i can't differentiate them with real frequency magnitudes. Please suggest me some method, or methodology to eliminate this problem

Input frequencies F1, F2 Expected frequencies F1,F2 Receive frequencies ,F1,F2,F1-F2,F1+F2

https://i.stack.imgur.com/1gb8r.jpg plot link that elaborate problem

Atif Javed
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  • Can you post a plot? It sounds like there is some inter mixing going on in frontend between your two input tones. – fstop_22 Jul 19 '19 at 13:13
  • https://imgur.com/3rYYNv2 here is the attached plot that elaborate my problem clearly ,Accordance with image i want to detect f1, f2 frequencies and want to remove f1+f2 and f1-f2. – Atif Javed Jul 22 '19 at 07:08
  • That kind of problem is not caused by analysis with FFT. The two frequencies have been mixed in a multiplicative way before you got to the FFT, and that produced the sum and difference frequencies you're seeing. In the data the FFT gets they are really there. If you are making this problem yourself via heterodyne mixing, then the usual practice is to choose a mixing frequency that puts the stuff you don't want in a band you can filter out. – Matt Timmermans Jul 23 '19 at 03:09
  • @MattTimmermans basically i want to detect that frequencies where communication happens, and maximum energy point in a band is my required frequency, In above scenario f1+f2 and f1-f2 is within my band but communication only happens at f1 f2. – Atif Javed Jul 24 '19 at 04:22

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Windowing can reduce windowing artifacts and distant side lobes, but makes the main lobe wider in exchange. But a large reduction in both the main-lobe and near side-lobes normally requires using more data and a longer FFT.

hotpaw2
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  • You are talking about spectral leakage that arises due to the effect on the FFT of the abrupt rising and falling edges of the rectangular window. By windowing the data before run them through an FFT routine, we can improve the sensitivity of your spectral measurements. But here i am talking about images that arises due to detection of multiple frequencies, attached image link will help you to understand the exact problem . This scenario is known as inter-modal distortion in radios – Atif Javed Jul 22 '19 at 07:39