Offset Stability in Mode-Split MEMS Gyroscopes

MEMS gyroscopes stability is crucial for long-term inertial navigation. This thesis explores the stability of the MEMS gyroscopes specific to the mode-split architecture, commonly used in mass market inertial sensors. It focuses on the offset stability of those devices and analyzes both systematic and stochastic offset contribution. One example of systematic effects is the change in environmental temperature, which can be compensated through system understanding. Thus, a temperature model of the gyroscope offset was developed and compared against the measurements of forty research devices. At the same time, stochastic contributions define the best-achievable limit for offset stability. To uncover the root causes of the bias instability, a scale factor instability model was derived and combined with a phase space gyroscope model. The scale factor instability model carries the information of the amplitude change of the signals in a gyroscope system, whereas the phase models the phase noise shaping. The combination of the two models resulted in a bias instability model applicable to both rate and quadrature signals. Based on the model prediction, bias instability improvement of up to 40 % was achieved, through the reduction of the PLL input phase flicker noise. The bias instability model was identified sensorindividually on four triaxial research gyroscope devices, equivalent to having twelve single axis devices. The proposed scale factor and bias instability models provide a measurement methodology to distinguish different flicker noise contributions. This methodology was successfully applied to available research devices at Robert Bosch GmbH, successfully identifying the dominant bias instability (flicker) noise sources. Depending on the system performance either temperature or flicker noise may be the limiting factors for long-term gyroscope rate signal stability. Hence, both the temperature and bias instability model represent a step towards gyroscope stability improvement, and in turn more precise navigation.