High Performance FM Gyroscopes

Abstract: 

MEMS gyroscopes are used in a wide range of applications such as gaming and image stabilization. However, the poor long-term stability of consumer MEMS gyroscopes precludes their use in demanding applications such as inertial navigation. Although devices with higher performance are available, they suffer from substantially higher power dissipation, size, and cost. For wider adoption it is imperative to find solutions that reduce drift without compromising the advantages of MEMS gyroscopes.

This thesis focuses on scale factor and bias stability. The scale factor of any sensor is set by a reference. Unfortunately, conventional amplitude modulated (AM) MEMS gyroscopes measure rate indirectly via the Coriolis force. In these solutions, the scale factor is set by many parameters including mass, spring constant, gaps, and, depending on the implementation, even absolute voltage. Achieving an accurate scale factor requires controlling all of these parameters, a most challenging task. The proposed solution measures rate—degrees per second, i.e. a frequency—directly . The scale factor is set explicitly by an external clock. Since very accurate clock sources are available, scale factor accuracy at the ppm level is readily achievable.

The second issue, bias stability, is addressed with a readout mechanism that implicitly modulates input rate, hence shifting its spectrum away from low-frequency drift sources such as temperature variations. The same approach is used in conventional precision gyroscopes under the name “may tagging”. Those solutions mount the gyroscope on a spinning platform that periodically rotates the transducer, thereby inverting its sensitivity. The proposed solution achieves the same without moving the transducer and hence is compatible with low cost planar MEMS implementations.

Publication date: 
December 1, 2019
Publication type: 
Ph.D. Dissertation
Citation: 
%0 Thesis %A Eminoglu, Burak %T High Performance FM Gyroscopes %I EECS Department, University of California, Berkeley %D 2019 %8 December 1 %@ UCB/EECS-2019-152 %U http://www2.eecs.berkeley.edu/Pubs/TechRpts/2019/EECS-2019-152.html %F Eminoglu:EECS-2019-152