Understanding analog to digital converter specifications
Confused by analogtodigital converter specifications? Here's a primer to help you decipher them and make the right decisions for your project.
Although manufacturers use common terms to describe analogtodigital converters (ADCs), the way ADC makers specify the performance of ADCs in data sheets can be confusing, especially for a newcomers. But to select the correct ADC for an application, it's essential to understand the specifications. This guide will help engineers to better understand the specifications commonly posted in manufacturers' data sheets that describe the performance of successive approximation register (SAR) ADCs.
ABCs of ADCs
ADCs convert an analog signal input to a digital output code. ADC measurements deviate from the ideal due to variations in the manufacturing process common to all integrated circuits (ICs) and through various sources of inaccuracy in the analogtodigital conversion process. The ADC performance specifications will quantify the errors that are caused by the ADC itself.
ADC performance specifications are generally categorized in two ways: DC accuracy and dynamic performance. Most applications use ADCs to measure a relatively static, DClike signal (for example, a temperature sensor or straingauge voltage) or a dynamic signal (such as processing of a voice signal or tone detection). The application determines which specifications the designer will consider the most important.
For example, a DTMF decoder samples a telephone signal to determine which button is depressed on a touchtone keypad. Here, the concern is the measurement of a signal's power (at a given set of frequencies) among other tones and noise generated by ADC measurement errors. In this design, the engineer will be most concerned with dynamic performance specifications such as signaltonoise ratio and harmonic distortion. In another example, a system may measure a sensor output to determine the temperature of a fluid. In this case, the DC accuracy of a measurement is prevalent so the offset, gain, and nonlinearities will be most important.
DC accuracy
Many signals remain relatively static, such as those from temperature sensors or pressure transducers. In such applications, the measured voltage is related to some physical measurement, and the absolute accuracy of the voltage measurement is important. The ADC specifications that describe this type of accuracy are offset error, fullscale error, differential nonlinearity (DNL), and integral nonlinearity (INL). These four specifications build a complete description of an ADC's absolute accuracy.
Although not a specification, one of the fundamental errors in ADC measurement is a result of the dataconversion process itself: quantization error. This error cannot be avoided in ADC measurements. DC accuracy, and resulting absolute error are determined by four specs—offset, fullscale/gain error, INL, and DNL. Quantization error is an artifact of representing an analog signal with a digital number (in other words, an artifact of analogtodigital conversion). Maximum quantization error is determined by the resolution of the measurement (resolution of the ADC, or measurement if signal is oversampled). Further, quantization error will appear as noise, referred to as quantization noise in the dynamic analysis. For example, quantization error will appear as the noise floor in an FFT plot of a measured signal input to an ADC, which I'll discuss later in the dynamic performance section).
The ideal transfer function
The transfer function of an ADC is a plot of the voltage input to the ADC versus the code's output by the ADC. Such a plot is not continuous but is a plot of 2^{N} codes, where N is the ADC's resolution in bits. If you were to connect the codes by lines (usually at codetransition boundaries), the ideal transfer function would plot a straight line. A line drawn through the points at each code boundary would begin at the origin of the plot, and the slope of the plot for each supplied ADC would be the same as shown in Figure 1.
Figure 1: Ideal transfer function of a 3bit ADC
Figure 1 depicts an ideal transfer function for a 3bit ADC with reference points at code transition boundaries. The output code will be its lowest (000) at less than 1/8 of the fullscale (the size of this ADC's code width). Also, note that the ADC reaches its fullscale output code (111) at 7/8 of full scale, not at the fullscale value. Thus, the transition to the maximum digital output does not occur at fullscale input voltage. The transition occurs at one code width—or least significant bit (LSB)—less than fullscale input voltage (in other words, voltage reference voltage).
Figure 2: 3bit ADC transfer function with  1/2 LSB offset
The transfer function can be implemented with an offset of  1/2 LSB, as shown in Figure 2. This shift of the transfer function to the left shifts the quantization error from a range of ( 1 to 0 LSB) to ( 1/2 to +1/2 LSB). Although this offset is intentional, it's often included in a data sheet as part of offset error (see section on offset error).
Limitations in the materials used in fabrication mean that realworld ADCs won't have this perfect transfer function. It's these deviations from the perfect transfer function that define the DC accuracy and are characterized by the specifications in a data sheet.
The DC performance specifications described have accompanying figures that depict two transfer function segments: the ideal transfer function (solid, blue lines) and a transfer function that deviates from the ideal with the applicable error described (dashed, yellow line). This is done to better illustrate the meaning of the performance specifications.
Offset error, fullscale error
The ideal transfer function line will intersect the origin of the plot. The first code boundary will occur at 1 LSB as shown in Figure 1. You can observe offset error as a shifting of the entire transfer function left or right along the input voltage axis, as shown in Figure 3.
Figure 3: Offset error
An error of  1/2 LSB is intentionally introduced into some ADCs but is still included in the specification in the data sheet. Thus, the offseterror specification posted in the data sheet includes 1/2 LSB of offset by design. This is done to shift the potential quantization error in a measurement from 0 to 1 LSB to  1/2 to +1/2 LSB. In this way, the magnitude of quantization error is intended to be < 1/2 LSB, as Figure 4 illustrates.
Figure 4: Quantization error vs. output code
Figure 5: Fullscale error
Fullscale error is the difference between the ideal code transition to the highest output code and the actual transition to the output code when the offset error is zero. This is observed as a change in slope of the transfer function line as shown in Figure 5. A similar specification, gain error, also describes the nonideal slope of the transfer function as well as what the highest code transition would be without the offset error. Fullscale error accounts for both gain and offset deviation from the ideal transfer function. Both fullscale and gain errors are commonly used by ADC manufacturers.
Nonlinearity
Ideally, each code width (LSB) on an ADC's transfer function should be uniform in size. For example, all codes in Figure 2 should represent exactly 1/8th of the ADC's fullscale voltage reference. The difference in code widths from one code to the next is differential nonlinearity (DNL). The code width (or LSB) of an ADC is shown in Equation 1.
(Equation 1)
The voltage difference between each code transition should be equal to one LSB, as defined in Equation 1. Deviation of each code from an LSB is measured as DNL. This can be observed as uneven spacing of the code "steps" or transition boundaries on the ADC's transferfunction plot. In Figure 6, a selected digital output code width is shown as larger than the previous code's step size. This difference is DNL error. DNL is calculated as shown in Equation 2.
Figure 6: Differential nonlinearity
(Equation 2)
The integral nonlinearity (INL) is the deviation of an ADC's transfer function from a straight line. This line is often a bestfit line among the points in the plot but can also be a line that connects the highest and lowest data points, or endpoints. INL is determined by measuring the voltage at which all code transitions occur and comparing them to the ideal. The difference between the ideal voltage levels at which code transitions occur and the actual voltage is the INL error, expressed in LSBs. INL error at any given point in an ADC's transfer function is the accumulation of all DNL errors of all previous (or lower) ADC codes, hence it's called integral nonlinearity. This is observed as the deviation from a straightline transfer function, as shown in Figure 7.
Figure 7: Integral nonlinearity error
Because nonlinearity in measurement will cause distortion, INL will also affect the dynamic performance of an ADC.
Absolute error
The absolute error is the total DC measurement error and is characterized by the offset, fullscale, INL, and DNL errors. Quantization error also affects accuracy, but it's inherent in the analogtodigital conversion process (and so does not vary from one ADC to another of equal resolution). When designing with an ADC, the engineer uses the performance specifications posted in the data sheet to calculate the maximum absolute error that can be expected in the measurement, if it's important. Offset and fullscale errors can be reduced by calibration at the expense of dynamic range and the cost of the calibration process itself. Offset error can be minimized by adding or subtracting a constant number to or from the ADC output codes. Fullscale error can be minimized by multiplying the ADC output codes by a correction factor. Absolute error is less important in some applications, such as closedloop control, where DNL is most important.
Dynamic performance
An ADC's dynamic performance is specified using parameters obtained via frequencydomain analysis and is typically measured by performing a fast Fourier transform (FFT) on the output codes of the ADC. In Figure 8, the fundamental frequency is the input signal frequency. This is the signal measured with the ADC. Everything else is noise—the unwanted signals—to be characterized with respect to the desired signal. This includes harmonic distortion, thermal noise, 1/ƒ noise, and quantization noise. (The figure is exaggerated for ease of observation.) Some sources of noise may not derive from the ADC itself. For example, distortion and thermal noise originate from the external circuit at the input to the ADC. Engineers minimize outside sources of error when assessing the performance of an ADC and in their system design.
Figure 8: An FFT of ADC output codes
Signaltonoise ratio
The signaltonoise ratio (SNR) is the ratio of the root mean square (RMS) power of the input signal to the RMS noise power (excluding harmonic distortion), expressed in decibels (dB), as shown in Equation 3.
(Equation 3)
SNR is a comparison of the noise to be expected with respect to the measured signal. The noise measured in an SNR calculation doesn't include harmonic distortion but does include quantization noise (an artifact of quantization error) and all other sources of noise (for example, thermal noise). This noise floor is depicted in the FFT plot in Figure 9. For a given ADC resolution, the quantization noise is what limits an ADC to its theoretical best SNR because quantization error is the only error in an ideal ADC. The theoretical best SNR is calculated in Equation 4.
Figure 9: SNR— A measure of the signal compared to the noise floor
SNR(dB)=6.02N+1.76 (4)
Where N is the ADC resolution
(Equation 4)
Quantization noise can only be reduced by making a higherresolution measurement (in other words, a higherresolution ADC or oversampling). Other sources of noise include thermal noise, 1/ƒ noise, and sample clock jitter.
Harmonic distortion
Nonlinearity in the data converter results in harmonic distortion when analyzed in the frequency domain. Such distortion is observed as "spurs" in the FFT at harmonics of the measured signal as illustrated in Figure 10. This distortion is referred to as total harmonic distortion (THD), and its power is calculated in Equation 5.
Figure 10: FFT showing harmonic distortion
(Equation 5)
The magnitude of harmonic distortion diminishes at high frequencies to the point that its magnitude is less than the noise floor or is beyond the bandwidth of interest. Data sheets typically specify to what order the harmonic distortion has been calculated. Manufacturers will specify which harmonic is used in calculating THD; for example, up to the fifth harmonic is common (see the example ADC specification in Table 1).
Table 1: Example: Silicon Labs C8051F060 16bit ADC electrical characteristics
Parameter  Conditions  MIN  TYP  MAX  UNITS 
DC accuracy  
Resolution  bits  
Integral nonlinearity () 
Singleended differential 
0.75 0.5 
2 1 
LSB LSB 

Integral nonlinearity () 
Singleended differential 
1.5 1 
4 2 
LSB  
Differential nonlinearity  Guaranteed monotonic  0.5  LSB  
Offset error  0.1  mV  
Fullscale error  0.008  %F.S.  
Gain temperature coefficient  TBD  ppm/ C  
Dynamic performance  Conditions  MIN  TYP  MAX  UNITS 
Signaltonoise plus distortion 
Fin = 10kHz, singleended Fin = 10kHz, differential 
86 89 
dB dB 

Total harmonic distortion 
Fin = 10kHz, singleended Fin = 10kHz, differential 
96 103 
dB dB 

Spuriousfree dynamic range 
Fin = 10kHz, singleended Fin = 10kHz, differential 
97 104 
dB dB 

CMRR  Fin = 10kHz  86  dB  
Channel isolation  100  dB  
Timing  Conditions  MIN  TYP  MAX  UNITS 
SAR clock frequency  MHz  
Conversion time in SAR clocks  clocks  
Track/hold acquisition time  ns  
Throughput rate  Msps  
Aperture delay  External CNVST signal  1.5  ns  
RMS aperture jitter  External CNVST signal  5  ps  
Analog inputs  Conditions  MIN  TYP  MAX  UNITS 
Input voltage range 
Singleended (AINAING) differential (AINAIN) 
0 VREF 
VREF VREF 
V V 

Input capacitance  80  pF  
Operating input range 
AIN or AIN AING or AING (DC only) 
0.2  AV+ 
V V 

Power specifications  Conditions  MIN  TYP  MAX  UNITS 
Power supply current (each ADC) 
Operating mode, Msps AV+ AVDD Shutdown Mode 
4.0 1.5 1 
mA mA mA 


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