Driving an A/D at multiples of the desired sample rate, plus processing needed to average results, can severely increase power consumption. Readings in a pressure sensor show how oversampling can increase ENOB. Here’s a table from the Bosch BMP390 datasheet, showing how oversampling can increase ENOB, pulling more bits of resolution out of a conversion. Oversampling the A/D and averaging the results into a single reading use the randomness of white noise to lower its intensity versus the desired signal. If it’s white noise, evenly distributed and not in a spike inside the sample rate range, statistics can be put to work. Low-pass filtering applied at the A/D input can reject harmonics beyond that range, leaving signals and noise spanning from near DC up to the sample rate. The minimum sample rate of an A/D converter should be twice the frequency of signals of interest, the Nyquist rate. How are accurate readings with these A/Ds in dynamic, noisy environments possible? Still, system noise can be higher than the theoretical best signal-to-noise ratio (SNR) of these higher resolution converters. For example, pressure sensors display significant non-linearities as temperature varies, and compensation is best done in software.įor many applications, 16-bit, 24-bit, or even 32-bit A/D converters are common today. Keep in mind that the sensor being read may have offset, gain, and non-linearity issues as well. Most A/D converters are trimmed for offset and gain errors at the factory and are designed to limit non-linearity. Integral non-linearity is a measure of how well conversion keeps straight-line performance against the analog input. If the differential linearity is off, it’s possible the A/D will have missing codes as a result, digital values that are skipped as the analog input voltages ramp up. First is differential non-linearity, where step widths aren’t exactly 1 LSB. The A/D offset and gain errors are a major source of static inaccuracies. Gain error affects every reading as a percentage, with the error value increasing at higher analog input levels.
After correcting offset error, full-scale digital output should match the full-scale analog input voltage. Offset error affects every reading by the same value. First is offset error, often called zero-scale error because a zero analog input voltage should result in a digital zero output.
Simple example: a 12-bit converter with 4,096 possible values samples a 10-V wide signal, setting a 2.44-mV step width and up to ☑.22-mV quantization error on each sample.īesides quantization error, there are several other sources of static errors. An A/D has to decide whether the LSB is a 1 or a 0, based on the closest available value. The higher the resolution, the bigger the chance there is some uncertainty in the least significant bits (LSBs) of a reading.Įven if there were zero system noise, there is quantization error built into any A/D converter. Riddle me this: when is a 12-bit A/D converter not a 12-bit A/D converter? More often than one might think in a real-world circuit, the effective number of bits (ENOB) usually turns out to be less than the stated bit resolution. An 8-bit converter plus a temperature sensor in a weather station might provide temperature readings to the nearest degree, while a 12-bit converter in the same setup could deliver readings to a tenth of a degree. Resolution relates to measurement precision. Several factors impact A/D converter accuracy, including resolution and quantization, offset and gain errors, non-linearity, and system noise. Now, what happens when an A/D fires up-how accurate are those readings? Getting good input data is critical to any project. The previous blog discussed how makers can select an A/D converter by understanding the application and how manufacturers optimize a part for that role.
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