Fast Fourier Transforms
TDS 420A, TDS 430A, TDS 460A & TDS 510A User Manual
3–39
To learn how to optimize your display of FFT data, read about how the FFT
windows data before computing the FFT math waveform.
Windowing Process. The oscilloscope multiplies the FFT time domain record by
one of four FFT windows before it inputs the record to the FFT function.
Figure 3–22 shows how the time domain record is processed.
The FFT windowing acts like a bandpass filter between the FFT time domain
record and the FFT frequency domain record. The shape of the window controls
the ability of the FFT to resolve (separate) the frequencies and to accurately
measure the amplitude of those frequencies.
Selecting a Window. You can select your window to provide better frequency
resolution at the expense of better amplitude measurement accuracy in your FFT,
better amplitude accuracy over frequency resolution, or to provide a compromise
between both. You can choose from these four windows: Rectangular, Hamming,
Hanning, and Blackman-Harris.
In step 8 (page 3–29) in Operation, the four windows are listed. In general,
choose a window that can just resolve between the frequencies you want to
measure. That way, you will have the best amplitude accuracy and leakage
elimination while still separating the frequencies.
You can often determine the best window empirically by first using the window
with the most frequency resolution (rectangular), and then proceeding toward
that window with the least (Blackman-Harris) until the frequencies merge. Use
the window just before the window that lets the frequencies merge for best
compromise between resolution and amplitude accuracy.
NOTE. If the Hanning window merges the frequencies, try the Hamming window
before settling on the rectangular window. Depending on the distance of the
frequencies you are trying to measure from the fundamental, the Hamming
window sometimes resolves frequencies better than the Hanning.
FFT Windows
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