Datasheet

AD7864
Rev. D | Page 21 of 28
DYNAMIC SPECIFICATIONS
The AD7864 is specified and 100% tested for dynamic perfor-
mance specifications as well as traditional dc specifications, such
as integral and differential nonlinearity. These ac specifications are
required for signal processing applications such as phased array
sonar, adaptive filters, and spectrum analysis. These applications
require information on the effect of the ADC on the spectral
content of the input signal. Thus, the parameters for which the
AD7864 is specified include SNR, harmonic distortion, inter-
modulation distortion, and peak harmonics. These terms are
discussed in more detail in the following sections.
SIGNAL-TO-NOISE RATIO (SNR)
SNR is the measured signal-to-noise ratio at the output of the
ADC. The signal is the rms magnitude of the fundamental.
Noise is the rms sum of all the nonfundamental signals up to
half of the sampling frequency (f
S
/2) excluding dc. SNR depends
on the number of quantization levels used in the digitization
process; the more levels, the smaller the quantization noise. The
theoretical signal-to-noise ratio for a sine wave input is given by
SNR = (6.02N + 1.76) dB (1)
where N is the number of bits.
Thus, for an ideal 12-bit converter, SNR = 74 dB.
Figure 16 shows a histogram plot for 8192 conversions of a dc
input using the AD7864 with a 5 V supply. The analog input was
set at the center of a code. The figure shows that all the codes
appear in the one output bin, indicating very good noise
performance from the ADC.
ADC CODE
1054
1
0
5
5
1
0
5
6
1
0
5
7
1
0
5
8
1
0
5
9
1
0
6
0
1
0
6
1
1
0
6
2
1
0
6
3
1
0
6
4
9000
8000
0
4000
3000
2000
1000
6000
5000
7000
COUNTS
01341-016
Figure 16. Histogram of 8192 Conversions of a DC Input
The output spectrum from the ADC is evaluated by applying a
sine wave signal of very low distortion to the analog input. A
fast fourier transform (FFT) plot is generated from which the
SNR data can be obtained. Figure 17 shows a typical 4096 point
FFT plot of the AD7864 with an input signal of 99.9 kHz and a
sampling frequency of 500 kHz. The SNR obtained from this
graph is 72.6 dB. Note that the harmonics are taken into
account when calculating the SNR.
0 50 100
–110
–100
–90
–80
–70
–60
–50
–40
–30
–20
–10
0
150
FREQUENCY (kHz)
(dB)
200 250
AD7864-1 @ 25°C
5V SUPPLY
SAMPLING AT 499,712Hz
INPUT FREQUENCY OF 99,857Hz
8192 SAMPLES TAKEN
01341-017
Figure 17. FFT Plot
EFFECTIVE NUMBER OF BITS
The formula given in Equation 1 relates the SNR to the number
of bits. Rewriting the formula, as in Equation 2, it is possible to
get a measure of performance expressed in effective number of
bits (N).
02.6
76.1
−
=
SNR
N
(2)
The effective number of bits for a device can be calculated
directly from its measured SNR. Figure 18 shows a typical plot
of effective number of bits vs. frequency for an AD7864-2.
FREQUENCY (kHz)
12
4
EFFECTIVE NUMBERS OF BITS
11
8
7
6
5
10
9
0 3000500
–40°C
+25°C
+105°C
1000 1500 2000 2500
01341-018
Figure 18. Effective Numbers of Bits vs. Frequency
INTERMODULATION DISTORTION
With inputs consisting of sine waves at two frequencies, fa and
fb, any active device with nonlinearities creates distortion products
at sum and difference frequencies of mfa ± nfb where m, n = 0,
1, 2, 3, and so forth. Intermodulation terms are those for which
neither m nor n are equal to zero. For example, the second-order