A mathematical model is established to study the impact of nonlinear errors on the performance of cyclic analog-to-digital converters (ADCs) and imaging quality of CMOS image sensors (CIS). And a radix-based foreground digital calibration method for cyclic ADCs in large array CIS is proposed and modeled. The nonlinear errors caused by capacitor mismatch and finite operational amplifier (OPAMP) gain are mainly studied. Simulation results show that the proposed calibration method based on the statistical characteristics of large array CIS can effectively reduce the influence of nonlinear errors, greatly improve ADC linearity under large capacitor mismatch and finite OPAMP gain. In a CIS with 1500 columns of parallel ADCs, when the capacitor mismatch and OPAMP gain are 1% and 40 dB respectively, the effective number of bits (ENOB) of the calibrated ADC can be increased from about 6bit to 13bit. These results provide a new guideline for the calibration of cyclic ADCs in large array CMOS image sensors.

建立了数学模型来研究非线性误差对循环模数转换器（ADC）的性能和CMOS图像传感器（CIS）的成像质量的影响。提出并建模了一种基于基数的大阵列CIS中循环ADC的前景数字标定方法。主要研究了由电容器失配和有限运算放大器（OPAMP）增益引起的非线性误差。仿真结果表明，基于大阵列CIS统计特性的校准方法可以有效减少非线性误差的影响，在较大的电容器失配和有限的OPAMP增益下，可以大大提高ADC的线性度。在具有1500列并行ADC的CIS中，当电容器失配和OPAMP增益分别为1％和40 dB时，校准后的ADC的有效位数（ENOB）可以从大约6位增加到13位。这些结果为校准大型阵列CMOS图像传感器中的循环ADC提供了新的指南。