# A Survey of Analog-to-Digital Converters for Operation under Radiation Environments
## 4 Data Analysis
### Radiation Performance  
TID is usually measured up to a predefined dose that can be lower than the maximum bearable before performance degradation. Something similar occurs with SEL characterization, where the maximum LET tested does not necessarily provoke latch-up events. SET and SEU tests have several degrees of freedom--test method, event detection criteria, sampling frequency, bias conditions, etc.--that make each ADC characterization very specific. In Table 2, we have listed the nine test methods used in the literature to evaluate the soft-error sensibility of adenv-ADCs; methods known by two different names are presented in the same line. Identified test methods for the _selection_ are collected in column 'SEE Test' of Table 1. Unfortunately, different test methods used for the same ADC give similar SET LET\({}_{th}\) but different SET cross-sections (even if within the same order of magnitude) [3; 37; 35; 34; 65]. In addition, SET/SEU cross-sections can depend on the sampling frequency of the ADC under test [34] and on the ionizing dose [5; 66]. Therefore, comparing radiation performance across devices shall be accomplished carefully. This variability in test complicates the extraction of patterns on radiation performance. \(\text{FOM}_{TID}\) and \(\text{FOM}_{SET}\) can be used as a first filter to compare performance, but a closer look is required when figures are close. Figure 5: Conversion energy against signal-to-noise and distortion ratio. Figure 6 plots the reported TID against nominal power consumption for each _selection_'s member. As expected, the best performing ADCs (slashed line), present greater TIDs for higher nominal power consumptions. However, power consumption is also related with other ADC parameters; the most important ones are included in \(\text{FOM}_{W}\) (\(f_{s}\) and ENOB). Since \(\text{FOM}_{TID}\) combines TID with \(\text{FOM}_{W}\), it can be used to evaluate the efficiency of an ADC including its TID performance. Figure 7 represents the calculated \(\text{FOM}_{TID}\) against nominal power consumption for each _selection_'s member. Just Boeing-1 ADC [50; 51] with \(8.85\times 10^{9}\) levels/mg surpasses the _selection_'s envelope (slashed line), established in \(2\times 10^{9}\) levels/mg by the rest of the best performing ADCs. This ADC is analyzed with other particular cases in Section 4.7. The fact that \(\text{FOM}_{W}\)'s envelope is constant across \(f_{s}\) for the _selection_ (see Figure 4) could help to extract patterns about \(\sigma_{sat}\), and hence \(\text{FOM}_{SET}\), across \(f_{s}\). SET and SEU data were both used to calculate \(\text{FOM}_{SET}\) due to the common physical phenomenon producing both effects. It is expected for both transients and upsets that \(\text{LET}_{th}\) and \(\sigma_{sat}\) envelopes increase with \(P\) and \(f_{s}\) respectively. Even if the _selection_ seems to behave so, the limited number of _selection_'s members characterized in transients and/or upsets does not allow to extract clear patterns about these effects. \begin{table}
\begin{tabular}{l l l l} \hline \hline \# & **Test Method** & **Abbreviation** & **Reference(s)** \\ \hline
1 & Beat Frequency/Two-Point & BF/2P & [34; 37; 65; 67] \\
2 & Code Error Rate/Coherent Sampling & CER/CS & [4; 51; 54; 68] \\
3 & Comparison with DAC input & DAC & [1] \\
4 & Comparison with ‘golden chip’ & GOLD & [69] \\
5 & Dynamic Input Signal & DIS & [70] \\
6 & Four-Point & 4P & [3; 34; 71; 72] \\
7 & Quasi-Static & QS & [36] \\
8 & Single-Point & 1P & [3; 34; 45] \\
9 & Static & S & [35; 37; 73; 74] \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Detection methods of soft errors in radenv-ADCs testing. Figure 6: Total ionizing dose against power consumption. Figure 8 plots the calculated \(\text{FOM}_{SET}\) for both SET and SEU against the nominal power consumption for each _selection_'s member.