Reset Noise Sampling Feedforward Technique (RNSF) for Low Noise MEMS Capacitive Accelerometer

Abstract

The reset noise sampling feedforward (RNSF) technique is proposed in this paper to reduce the noise floor of the readout circuit for micro-electromechanically systems (MEMS) capacitive accelerometer. Because of the technology-imposed size restriction on the sensing element, the sensing capacitance and the capacitance variation are reduced to the femto-farad level. As a result, the reset noise from the parasitic capacitance, which is pico-farad level, becomes significant. In this work, the RNSF technique focuses on the suppression of the parasitic-capacitance-induced noise, thereby improving the noise performance of MEMS capacitive accelerometer. The simulation results show that the RNSF technique effectively suppresses the thermal noise from the parasitic capacitance. Compared with the traditional readout circuit, the noise floor of the readout circuit with the RNSF technique is reduced by 9 dBV. The presented circuit based on the RNSF technique is fabricated by a commercial 0.18-μm BCD process and tested with a femto-farad MEMS capacitive accelerometer. The physical measurement results show that, compared with the readout circuit without the RNSF technique, the RNSF technique reduces the noise floor of the readout circuit for MEMS capacitive accelerometer from −72 dBV to −80 dBV. Compared with other similar works, the proposed readout circuit achieves better FoM (FoM=(power×noise floor)/system bandwidth=490 μW·μg/Hz) among the switched-capacitor readout circuits.