Using Dynamic Parameters to Measure Digitizer Performance

Much confusion exists about characterizing the performance of a highspeed digitizer device. Nominal vertical resolution is routinely presented as an indicator of a digitizer’s performance, but the relevance of this parameter is dubious since a digitizer’s true performance is characterized by the Dynamic Parameters*.

The Digital Storage Oscillo scope (DSO), a widely used digitizerlike device, is optimized for the visualization of unknown signals¹. The relatively low 8-bit nominal vertical resolution of the DSO (and ENOB of 6~7) is sufficient for signal visualization and may be offered at the highest sampling rates (~80 Giga - Samples/second). As a result, DSO product specifications typically emphasize their high input bandwidth and rarely list their vertical performance parameters. By contrast, digitizers are usually optimized for the rapid acquisition and analysis of small changes in broadly-known signals. While providing lower maximum sampling rates, digitizers typically offer higher vertical resolutions of 12-, 14-, and 16-bits.

 It is important to distinguish between the absolute accuracy and relative accuracy of a digitizer device. The absolute accuracy of a digitizer describes how close its measured voltage values are to the true MKS voltage reference values. By contrast, its relative accuracy specifies the fidelity of the shape of the acquired waveform with no reference to absolute voltage values. Using on-board calibration techniques, high-speed digitizers may achieve absolute accuracies of order 0.1% of the full-scale input voltage range. In the majority of digitizer applications, users are concerned not with the absolute accuracy but rather with the relative accuracy, which in turn is specified by the Dynamic Parameters.

Generally speaking, the fidelity of the signal acquired by a digitizer device may be compromised by three distinct factors:

1. Addition of random noise by the digitizer;
2. Distortion of the signal by the digitizer itself;
3. Irregularities in the time intervals at which samples are converted.

Figure 1. Typical examples of Moise and Distortion on a pure sine wave signal.

The distinction between signal noise and signal distortion is illustrated in Figure 1. The figure shows a pure sine wave, together with a sine wave that has been compromised by the addition of broadband signal noise and by signal distortion. Distortion is shown as attenuation near the input range limits, which is the typical precursor to signal clipping.