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Temperature-dominated drift is generally the main error source for high-performance micromachined resonant accelerometers (MRAs) due to inherent thermal stress effect of resonator structure and die-attach process. This paper describes a design and experimental evaluation of a temperature compensation scheme for MEMS resonant accelerometers that demonstrates excellent bias and scale factor stability against temperature variation. An on-chip temperature sensor fabricated by sputtering platinum film on glass substrate is proposed to accurately sense the temperature-induced frequency change of the resonator. Post-compensation algorithm is used to suppress the temperature sensitivity of the MRA over dynamic temperature environment. The temperature drift test and compensation of four MEMS accelerometers with navigation-grade performance in a range from -40 to 60 °C show that the stability of bias and scale factor has been improved greatly. Temperature compensation results with a polynomial fitting model and a convolutional neural network (CNN) model are presented and compared to suppress the temperature drift hysteresis in consecutive temperature-varying tests. These experimental results indicate that this resonant accelerometer exhibits excellent temperature stability after compensation, which offers the promise for high-performance inertial navigation applications.

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