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3.2
Coherent Input Frequency Selection
ADC Evaluation
Typical ADC analysis requires users to collect the resulting time-domain data and perform a Fourier
transform to analyze the data in the frequency domain. A stipulation of the Fourier transform is that the
signal must be continuous-time; however, this is not practical when looking at a finite set of ADC samples,
usually collected from a logic analyzer. Consequently, users typically apply a window function to minimize
the time-domain discontinuities that arise when analyzing a finite set of samples. For ADC analysis,
window functions have their own frequency signatures or lobes that distort both SNR and SFDR
measurements fo the ADC.
TI uses the concept of coherent sampling to work around the use of a window function. The central
premise of coherent sampling entails that the input signal into the ADC is carefully chosen such that when
a continuous-time signal is reconstructed from a finite sample set; no time-domain discontinuities exist. To
achieve this, the input frequency must be an integer multiple of the ratio of the ADC's sample rate (f
s
) and
the number of samples collected from the logic analyzer (N
s
). The ratio of f
s
to N
s
is typically referred to as
the fundamental frequency (f
f
). Determining the ADC input frequency is a two-step process. First, the
users select the frequency of interest for evaluating the ADC; then they divide this by the fundamental
frequency. This typically yields a non-integer value, which should be rounded to the nearest odd,
preferably prime, integer. Once that integer, or frequency bin (f
bin
), has been determined, users multiply
this with the fundamental frequency to obtain a coherent frequency to program into their ADC input signal
generator. The procedure is summarized as follows.
f
f
= f
s
/N
s
f
bin
= Odd_round(f
desired
/f
f
)
Coherent frequency = f
f
×
f
bin
SLAU196 – April 2007
11
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