Robust digital calibration engine for MEMS inertial sensor systems

Heinssen, Sascha; Hellwege, Nico; Heidmann, Nils; Paul, Steffen; Peters-Drolshagen, Dagmar

doi:10.1109/icsens.2015.7370520

Cited by 4 publications

(1 citation statement)

References 10 publications

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“…An orthogonal pseudo-random signal is placed in the signal path while operating, and only the output by the pseudo-random signal is separated using the orthogonal characteristic from the combined output to compensate for the gain variation of the Op Amp caused by temperature without using an additional temperature sensor. Then, the gain of Op Amp can be calculated and compensated from the separated signal [26]. Correlated double sampling (CDS) is a widely used low-frequency noise-reduction method.…”

Section: Signal-to-noise Ratio (Snr): Internal Noisementioning

confidence: 99%

Readout Circuits for Capacitive Sensors

Yoo

Choi

2021

Micromachines

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The development of microelectromechanical system (MEMS) processes enables the integration of capacitive sensors into silicon integrated circuits. These sensors have been gaining considerable attention as a solution for mobile and internet of things (IoT) devices because of their low power consumption. In this study, we introduce the operating principle of representative capacitive sensors and discuss the major technical challenges, solutions, and future tasks for a capacitive readout system. The signal-to-noise ratio (SNR) is the most important performance parameter for a sensor system that measures changes in physical quantities; in addition, power consumption is another important factor because of the characteristics of mobile and IoT devices. Signal power degradation and noise, which degrade the SNR in the sensor readout system, are analyzed; circuit design approaches for degradation prevention are discussed. Further, we discuss the previous efforts and existing studies that focus on low power consumption. We present detailed circuit techniques and illustrate their effectiveness in suppressing signal power degradation and achieving lower noise levels via application to a design example of an actual MEMS microphone readout system.

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Section: Signal-to-noise Ratio (Snr): Internal Noisementioning

confidence: 99%