MT-002 Datasheet, PDF (6/12 Pages) Analog Devices – What the Nyquist Criterion Means to Your Sampled Data System Design

MT-002
The Nyquist bandwidth is defined to be the frequency spectrum from dc to f_s/2. The frequency
spectrum is divided into an infinite number of Nyquist zones, each having a width equal to 0.5f_s
as shown. In practice, the ideal sampler is replaced by an ADC followed by an FFT processor.
The FFT processor only provides an output from dc to f_s/2, i.e., the signals or aliases which
appear in the first Nyquist zone.
Now consider the case of a signal which is outside the first Nyquist zone (Figure 5B). The signal
frequency is only slightly less than the sampling frequency, corresponding to the condition
shown in the time domain representation in Figure 4. Notice that even though the signal is
outside the first Nyquist zone, its image (or alias), f_s – f_a, falls inside. Returning to Figure 5A, it
is clear that if an unwanted signal appears at any of the image frequencies of f_a, it will also occur
at f_a, thereby producing a spurious frequency component in the first Nyquist zone.
This is similar to the analog mixing process and implies that some filtering ahead of the sampler
(or ADC) is required to remove frequency components which are outside the Nyquist bandwidth,
but whose aliased components fall inside it. The filter performance will depend on how close the
out-of-band signal is to f_s/2, and the amount of attenuation required.
BASEBAND ANTIALIASING FILTERS
Baseband sampling implies that the signal to be sampled lies in the first Nyquist zone. It is
important to note that with no input filtering at the input of the ideal sampler, any frequency
component (either signal or noise) that falls outside the Nyquist bandwidth in any Nyquist zone
will be aliased back into the first Nyquist zone. For this reason, an antialiasing filter is used in
almost all sampling ADC applications to remove these unwanted signals.
Properly specifying the antialiasing filter is important. The first step is to know the
characteristics of the signal being sampled. Assume that the highest frequency of interest is f_a.
The antialiasing filter passes signals from dc to f_a while attenuating signals above f_a.
Assume that the corner frequency of the filter is chosen to be equal to f_a. The effect of the finite
transition from minimum to maximum attenuation on system dynamic range is illustrated in
Figure 6A.
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