How to select ADC resolution, considering input signal SNR and digital signal processing?

Question

What I knew: The ADC resolution selection depends on the ADC inherent noise and input signal SNR.

Our application: Very high precision measurement of signals ranging 1kHz to 10kHz. We want to get as accurate result as possible, even 24-bit result.

The above statement, however, does not take digital signal processing after ADC sampling into consideration.

Since DSP techniques such as FIR, FFT and etc. may reduce the noises greatly, is it possible that increasing ADC resolution may also improve the measurement result when taking DSP techniques into consideration?

Answer 1

A general rule of thumb is that is you want something to not contribute to your noise budget, that it must be at least a factor of 10 higher SNR than the dominant noise source in your signal chain. As an example, if you have a signal source that is at 300 :1 SNR, run your ADC at 3000:1 and for all intents and purposes you can ignore the ADC.

The only way to do this properly is to do a noise analysis.

Post processing (via in DSP for example) has the potential to extract out salient features from above the noise but you have to be careful. You have to have sufficient bit depth so you don't introduce rounding/truncation errors. You have to ensure that you are conserving the nature of the noise (gaussian/poisson pdf) or else the noise floor may rise in an unpredictable way and may not be amenable to DSP techniques. These sorts of steps (matched filters etc.) typically at best can improve the SNR by factors of \$ \sqrt{N} \$ and often the processing cost (# of operations) often follows \$ N^2 \$ so these sorts of steps often become rapidly very expensive. But agains a proper analysis will show this.

I would caution you against assuming that a DSP technique will automatically reduce your noise. It is very important that you lot at your noise sources via histogram analysis to ensure that the PDF (Probability Density Function) is amenable to processing. I.e. it appears well behaved, Gaussian or Poisson, is not multivariate and is stationary

Answer 2

ADC resolution all depends on your application. Quite frankly, if your using something that is going to produce a wide value range, like sound or high frequency you will need a ADC with a higher resolution. If your just trying to take readings from something like a RTD sensor, you will likely have no need for a high resolution device and can save cost. One thing to take in consideration too is that typically higher resolution ADC's have slower sampling times. So you get a more precise reading, but not as many as them in the specified time period. If this was the case with audio, a higher resolution ADC would increase bandwidth, but decrease the bit rate. Your other concerns can be addressed though other circuitry options like filters and such. But like I said before, it is all in what your application actually is.

Answer 3

• Having an ADC that has better resolution than the external signal noise is a waste of money.
• Having an ADC that has poor resolution and hence high inherent SNR can be countered by increasing the sampling rate of your process and implementing software recovery of the signal through filtering.
• If your signal bandwidth is known then a lot more can be done in algorithms to improve SNR by excluding noise - this is basically what an FFT does and software radio.

As we don't know much about your application it seems pointless pouring out detail that doesn't apply.

Answer 4

To get 24 bit precision you probably want a ΣΔ-ADC (Sigma-Delta ADC). Which is a special kind of 1-bit ADC (with noise-shaping) followed by filtering of the digital values.

The advantage of the ΣΔ-ADC is that with just one bit the quantization can't be nonlinear.