we used the example
where we needed to digitize an analog input signal in the range of
0-1V and that digital samples are represented as 8-bits values and we found
that 0.003922V ( 1V/255 ) is the resolution of our ADC.
Obviously in our example
ADC number of bits ( 8 bits ) and the analog input signal range of
0-1V drives the resolution of our ADC ( 0.003922V ) and all of
this represents the most basic error budget of our ADC( or any ADC for that
matter ).
- So the conclusion here is that ADC number of bits
( 8 bits ) and analog input signal range of 0-1V drive how much error
in measurement is introduced by our ADC .
It would be nice to
represent this ADC error in measurement with one single number for example a percentage
of the analog input signal range of 0-1V of our ADC and to do this we can
use a following formula:
ADC error [%] = 100*
( analog input signal range )/2^^(ADC number of bits)
=> for our
example: ADC error [%] = 100*( 1V -0V) /( 2^^8 -1 ) = 0.3922%
By looking into this
simple formula it is clear that we could make a smaller ADC error
[%] if we do one of two things ( or both of them in the same time ):
- decrease ADC analog input signal range
- increase ADC number of bits
e.g. If we increase ADC analog
input signal range from 0-1V to 0-0.25V the ADC error will
decrease from 0.3922% to 0.1% :
=> ADC error [%]
= 100*( 0.25V -0V ) /( 2^^8 -1 ) = 0.1%
As a conclusion:
- if you come across that somebody is talking about,
for example an ADC error budget of 12 bits or 0.024% what they really mean
is the ADC error budget of 12 bits ADC for the input signal range
of 0-1V is 0.024% because:
=> ADC error [%]
= 100*( 1V -0V) /( 2^^12 -1 ) = 0.024%
© 2011-2020 ASIC Stoic. All rights reserved
© 2011-2020 ASIC Stoic. All rights reserved
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