Where do harmonics appear in the FFT spectrum?
While carrying out FFT spectrum of a signal, harmonics of a frequency appear at higher frequencies than fundamental frequency. My question is if fundamental frequency is the highest one in the signal, what would harmonics of that fundamental frequency signify in the signal?
What does Fourier transform do to a signal?
The physical meaning of the decomposition is, that if you add sines and cosines with the respective frequency of the FFT bins, and the respective amplitude of the FFT bins, you get back your original signal. Fourier transform is no more or no less than a decomposition of the signal in sines and cosines.
How are harmonics used in the AM signal?
You use a local oscillator, at the receiver, to create harmonics of the SSB signal spectrum, and then you adjust the oscillator frequency until you combine an upper sideband and lower sideband of that SSB signal, to re-create the original double sideband AM baseband spectrum. In short, the existence of harmonics is not necessarily bad news.
How are harmonics created in a single sideband signal?
A similar effect occurs when demodulating single sideband. You use a local oscillator, at the receiver, to create harmonics of the SSB signal spectrum, and then you adjust the oscillator frequency until you combine an upper sideband and lower sideband of that SSB signal, to re-create the original double sideband AM baseband spectrum.
What does the presence of harmonics in the Fourier transform mean?
When the Fourier Transform (or FFT) shows the presence of harmonics, it simply means that SOMETHING in the circuit creates this extra energy. The presence of harmonics may be completely to be expected, and may require additional means to deal with them.
When does a Fourier transform have a peak?
Fourier transform is no more or no less than a decomposition of the signal in sines and cosines. Eg, if I have any signal, and its fourier transform only has peaks around 100 Hz, 200 Hz, 300 Hz, with complex values a100, a200, a300, I can decompose the signal as:
How to calculate the FFT of a signal?
If you choose your FFT length to match your known range (so that k → 3.45 and k + 1 → 3.50 and k − 1 → 3.4, then you should be good to go.