AD-03 datasheet(3/4 Pages) NSC

Numer części	AD-03

Szczegółowy opis	Effects of Aperture Time and Jitter in a Sampled Data System

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3) Down convert to an I.F. of 1MHz then digitize at a rate

of 1MHz.

In this method, some of the advantages of

digital down conversion can be retained - multiple

channels can be demodulated simultaneously - and

complexity is reduced from a system that down converts

to baseband. From an aperture standpoint we are still

seeing input slew rates an order of magnitude greater

than we did in example 1, but two orders of magnitude

less than those seen in example 2.

4) Place a sample and hold circuit, sampling at a rate

of 1MHz, in front of the A/D in scenario 2. This results in

the A/D converter seeing a very low slew rate, but the

aperture errors are shifted to the sample-and-hold circuit.

In many cases a sample-and-hold has much lower

aperture errors associated with it than a comparable

speed A/D converter.

In all of the above scenarios, the digital output from the

converter is at a 1 MHz rate and the digital output would

be identical if the A/D converter were an ideal converter

with no aperture jitter. With real world converters, there

will be a vast difference in the signal to noise ratio in each

of these three scenarios.

The solution involving placing a sample and hold circuit in

front of an A/D converter is especially interesting with many

high speed, high resolution, monolithic A/D converters.

Many of these devices have particularly poor aperture

performance and as a result even if the input frequencies

are reduced to sub-nyquist rates, the aperture error may

be the dominant error source. Use of a separate sample

and hold will allow for the burden of sampling the signal

to be shifted to the sample and hold, reducing the

sensitivity to aperture jitter in the A/D converter.

Reducing Noise Through Signal Processing

A/D converter outputs contain noise that has as its

origins quantization noise, noise that comes from

aperture related effects and noise from other sources.

Often it is desirable to lump all of these together and just

treat them as noise and work towards reducing them.

One technique that can be used for this is simply to over-

sample the input then digitally low pass filter the output.

If we take the example above, where we have a 100MHz

carrier modulated with a 100kHz signal, if we sample at

a rate of 2MHz instead of a rate of 1 MHz, the noise is

distributed over a band that is twice as wide.

If the

digital signal is then filtered, and the half of the band that

does not contain the signal of interest is thrown away, the

result is a 3dB improvement in the signal to noise level.

This could be carried on as far as the speed of the

converter permits with the cost being carried mainly in

the power and complexity of the digital filtering hardware.

Imagine sampling the signal at 1GHz, then filtering out all

but the lowest 500kHz band to obtain the equivalent of

1MHz sampling: we would be able to obtain a 30dB

improvement in SNR over what we would have sampling

at 1MHz.

Another signal conditioning method that can be used

toreduce the noise both from aperture effects as well as

other sources is implemented in SD A/D converters. A

block diagram of a simple converter is shown in Figure 3.

Figure 3

If we replace the SD A/D and D/A pair with a simple

additive noise where this noise represents the noise

contributed by the sampling process, both quantization

noise and aperture jitter related noise, then the block

diagram is modified to look like that in Figure 4. The

transfer function for the signal in this system is given by:

Figure 4

It can be seen from this that if H(s) is large for the

frequency range in which the signal is, then the signal

transfer function is near unity.

The noise however, sees a different transfer function:

If H(s) is large in the area of interest then the noise is

attenuated in this same area.

The result is that the

signal to noise ratio is increased.

If an analysis is done of this (which is beyond the scope

of this paper) it turns out that this is a much more effec-

tive method of reducing the noise than the simple over-

sampling and low pass filtering that is outlined above.

With a first order filter for H(s) then the SNR improvement

that can be realized with

Σ∆ techniques is 9dB per octave

of oversampling as compared to the 3dB that we

obtained above. As the order of the filter used increases

the gains can be increased as well.

Conclusion

As digitizing systems increase in speed, aperture effects

play a larger and larger role in the total error budget of

the system. Techniques for analysis and prediction of

the errors have been presented.

Techniques for the

reduction of aperture related errors have been presented.

Signal

In

H(s)

A/D

D/A

Digital

Out

+

STF

Hs

1H S

=

()

+

()

Signal

In

H(s)

Sampling & Quantization

Noise In

Out

++

NTF

1

1H S

=

+

()

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