In recent years, the application prospects of high-precision MEMS gyroscopes have been shown to be very broad, but the large temperature drift of MEMS gyroscopes limits their application in complex temperature environments. In response to this, we propose a method that combines mode reversal and real-time multiple regression compensation to compensate for the temperature drift of gyroscope bias. This method has strong adaptability to the environment, low computational cost, the algorithm is online in real time, and the compensation effect is good. The experimental results show that under the temperature cycle of −20~20 °C and the temperature change rate of 4 °C/min, the method proposed in this paper can reduce the zero-bias stability from about 27.8°/h to 0.4527°/h, and the zero-bias variation is reduced from 65.88°/h to 1.43°/h. This method improves the zero-bias stability of the gyroscope 61-fold and the zero-bias variation 46-fold. Further, the method can effectively suppress the zero-bias drift caused by the heating of the gyroscope during the start-up phase of the gyroscope. The zero-bias stability of the gyroscope can reach 0.0697°/h within 45 min of starting up, and the zero-bias repeatability from 0 to 5 min after startup is reduced from 0.629°/h to 0.095°/h.

This paper is devoted to discussing the influence of thermal stress on the performance of the Butterfly Vibratory Gyroscope (BFVG). In many gyroscopes, due to the material properties and the fabrication processes, the deformation caused by residual stress or thermal mechanical stress is of great concern since it directly affects the performance. Here, a new stress-released structure was proposed to reduce the deformation to improve BFVG’s performance considering the symmetry of the electrode and the miniaturization of the structure. Its dimensional parameters relate to the effect of thermal stress release and the stiffness characteristics of the BFVG’s oblique beam. The single parameter analysis method was used to explore the influence of the parameters on the effect of thermal stress release to guide the optimal size of the final design. The effect of thermal stress release in the BFVG at the full range temperature was also tested after the fabrication. The results showed that the influence of thermal stress on the BFVG’s performance effectively reduced.

The butterfly gyroscope is simple to manufacture and it is considered as one kind of MEMS gyroscope with high sensitivity due to its unique structure. In reality, fabrication imperfections result in non-ideal geometries in the resonator, which in turn causes the quadrature error. The quadrature error has a great influence on the performance of the sensors in Micro and Nano scale, such as the zero-rate output (ZRO), the detection resolution and the dynamic range. However, the fact that the mechanical parameters of resonators are unknown (due to fabrication variation, fluctuations with temperature and aging) poses serious challenges. This paper presents a simple, yet effective method of quadrature compensation in butterfly resonator by electrostatic tuning. Theoretical calculation of quadrature error in butterfly gyroscope is carried out, establishing the mathematical model of quadrature compensation. Then, the simulation analysis is conducted to further analyze the mechanism of quadrature error and the method of quadrature compensation. Also, 5 butterfly gyroscopes fabricated on the same silicon wafer are selected for the experiment of quadrature compensation and the ZRO of the butterfly gyroscopes improves up to two orders of magnitude with quadrature cancellation, showing the feasibility of the proposed approach to quadrature compensation in the butterfly gyroscope. Finally, the way to decrease the direct current voltage V_T required for suppressing the quadrature error is discussed. What is more, the method is not only suitable for the butterfly gyroscope, but also can be applied to other sensors in the Micro and Nanoscale.

Micro-Shell Resonator Gyroscopes have obvious SWaP (Size, Weight and Power) advantages and applicable accuracy for the autonomous navigation of Unmanned Ground Vehicles (UGVs), especially under GNSS-denied environments. When the Micro-Shell Resonator Gyroscope Rotary Inertial Navigation System (MSRG–RINS) operates in the whole-angle mode, its bias varies as an even-harmonic function of the pattern angle, which leads to difficulty in estimating and compensating the bias based on the MSRG in the process of attitude measurement. In this paper, an attitude measurement method based on virtual rotation self-calibration and rotary modulation is proposed for the MSRG–RINS to address this problem. The method utilizes the characteristics of the two operating modes of the MSRG, the force-rebalanced mode and whole-angle mode, to perform virtual rotation self-calibration, thereby eliminating the characteristic bias of the MSRG. In addition, the reciprocating rotary modulation method is used to suppress the residual bias of the MSRG. Furthermore, the magnetometer-aided initial alignment of the MSRG–RINS is carried out and the state-transformation extended Kalman filter is adopted to solve the large misalignment-angle problem under magnetometer assistance so as to enhance the rapidity and accuracy of initial attitude acquisition. Results from real-world experiments substantiated that the proposed method can effectively suppress the influence of MSRG’s bias on attitude measurement, thereby achieving high-precision autonomous navigation in GNSS-denied environments. In the 1 h, 3.7 km, long-range in-vehicle autonomous navigation experiments, the MSRG–RINS, integrated with a Laser Doppler Velocimetry (LDV), attained a heading accuracy of 0.35° (RMS), a horizontal positioning error of 4.9 m (RMS), and a distance-traveled accuracy of 0.24% D.