NOTE: Using windowing:
The theoretical requirement for inverse FFT is for the data to extend from zero
frequency to infinity. Side lobes appear around a discontinuity due to the fact
that the spectrum is cut off at a finite frequency. Windowing reduces the side
lobes by smoothing out the sharp transitions at the beginning and end of the
frequency sweep. As the side lobes are reduced the main lobe widens thereby
reducing the resolution.
In situations where there may be a small discontinuity close to a large one, side
lobe reduction Windowing should be used. When distance resolution is critical
Windowing can be reduced. The types of Windowing in order of increasing side
lobe reduction are: rectangular, nominal side lobe, low side lobe, minimum side
lobe. Figures 3-7 thru 3-10, on pages 3-11 and 3-12, are examples of the types
of Windowing.
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Chapter 3 Functions and Operations
