Root-Causes of Bias Instability Noise in Mode-Split MEMS Gyroscopes

This paper presents a general instability model of mode-split MEMS gyroscopes. The proposed model can accurately predict the bias instability of a given device based on the applied angular rate and system parameters. The model consists of two noise models: bias instability and scale factor instabili...

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Bibliographic Details
Published inJournal of microelectromechanical systems Vol. 33; no. 5; pp. 514 - 523
Main Authors Vujadinovic, Milos, Hiller, Tobias, Balslink, Thorsten, Elsobky, Mourad, Blocher, Lukas, Buhmann, Alexander, Northemann, Thomas, Choubey, Bhaskar
Format Journal Article
LanguageEnglish
Published IEEE 01.10.2024
Subjects
1/f noise
Allan deviation
analytical model
bias instability
Demodulation
flicker noise
gyroscope
Gyroscopes
MEMS inertial sensor
Micromechanical devices
mode-split
Noise
Phase locked loops
phase noise
phase space
Resonant frequency
scale factor instability
sensitivity
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Summary:This paper presents a general instability model of mode-split MEMS gyroscopes. The proposed model can accurately predict the bias instability of a given device based on the applied angular rate and system parameters. The model consists of two noise models: bias instability and scale factor instability. Four flicker noise sources are considered that are the most significant contributors. These include phase flicker noise of the drive capacitance to voltage converter, sense analog-to-digital (ADC) scale factor instability, proof mass voltage flicker noise, and additive flicker noise. All the noise contributors are thoroughly analyzed and experimentally characterized on four triaxial research devices. Based on the results of the experimental characterization, the proposed scale factor and bias instability models are verified against the measurement data. We find a good match between the presented model and measurements. As anticipated by the proposed model, a reduction of the phase flicker noise of the drive capacitance to voltage converter has led to up to 50% improvement in bias instability.[2024-0018]
ISSN:1057-7157
1941-0158
DOI:10.1109/JMEMS.2024.3406584