Exploiting Smallest Error to Calibrate Non-linearity in SAR ADCs

Hua Fan, Jingtao Li, Quanyuan Feng, Xiaopeng Diao, Lishuang Lin, Kelin Zhang, Haiding Sun, Hadi Heidari

Research output: Contribution to journalArticlepeer-review

9 Scopus citations


This paper presents a statistics-optimised organisation technique to achieve better element matching in Successive Approximation Register (SAR) Analog-to-Digital Converter (ADC) in smart sensor systems. We demonstrate the proposed technique ability to achieve a significant improvement of around 23 dB on Spurious Free Dynamic Range (SFDR) of the ADC than the conventional, testing with a capacitor mismatch σu = 0.2% in a 14 bit SAR ADC system. For the static performance, the max root mean square (rms) value of differential nonlinearity (DNL) reduces from 1.63 to 0.20 LSB and the max rms value of integral nonlinearity (INL) reduces from 2.10 to 0.21 LSB. In addition, it is demonstrated that by applying grouping optimisation and strategy optimisation, the performance boosting on SFDR can be effectively achieved. Such great improvement on the resolution of the ADC only requires an off-line pre-processing digital part.
Original languageEnglish (US)
Pages (from-to)42930-42940
Number of pages11
JournalIEEE Access
StatePublished - Jul 3 2018

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01
Acknowledgements: The work of Hua Fan was supported by the National Natural Science Foundation of China (NSFC) under Grant 61771111, as well as supported by China Postdoctoral Science Foundation under grant 2017M612940 and Special Foundation of Sichuan Provincial Postdoctoral Science Foundation. The work of Quanyuan Feng was supported by the National Natural Science Foundation of China (NSFC) under Grant 61531016, supported by the project of Science and Technology Support Program of Sichuan Province under Grant 2018GZ0139, and in part by the Sichuan Provincial Science and Technology Important Projects under Grant 2017GZ0110.


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