A 1/f noise optimized correlated multiple sampling technique for CMOS
image sensor
Abstract
Summary: This paper proposes a 1/f noise optimized correlated
multiple sampling (NOCMS) technique based on differentiated sampling
weights for CMOS image sensor. Transfer functions of standard CMS and
NOCMS for analyzing the suppression effect of random noise respectively
are derived based on the Fourier Transform theory. NOCMS shows a
dramatic advantage in the suppression of 1/f noise. For implementing
NOCMS, the ramp generator provides multiple sets of ramps with different
slopes to quantize the reset and signal voltages. Sampling weights are
increased with the decrease of ramp slopes. The last reset and first
signal values are weighted more due to their potentially higher
correlations. Simulation results under 110nm CMOS technology illustrate
that the ADC achieves DNL of −0.80/+0.70LSB and INL of −0.70/+0.90LSB
after the NOCMS operation. The input-referred random noise is 142.9µV
rms under standard CMS and 120.9µV rms
under NOCMS when the number of samples equals 8. The noise reduction
effect is improved by 15%. NOCMS makes it possible to further reduce
1/f noise of CMOS image sensor.