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Technological capabilities of manufacturing microelectromechanical system (MEMS) gyroscopes are still insufficient if compared to manufacturing high-efficient gyroscopes and accelerometers. This creates weaknesses in their mechanical structure and restrictions in the measurement accuracy, stability and reliability of MEMS gyroscopes and accelerometers. This paper aims to develop a new architectural solutions for optimization of MEMS gyroscopes and accelerometers and propose a multi-axis MEMS inertial module combining the functions of gyroscope and accelerometer.

The finite element modeling (FEM) and the modal analysis in FEM are used for sensing, drive and control electrode capacitances of the multi-axis MEMS inertial module with the proposed new architecture. The description is given to its step-by-step process of manufacturing. Algorithms are developed to detect its angular rates and linear acceleration along three Cartesian axes.

Experimental results are obtained for eigenfrequencies and capacitances of sensing, drive and control electrodes for 50 manufactured prototypes of the silicon electromechanical sensor (SES). For 42 SES prototypes, a good match is observed between the calculated and simulated capacitance values of comb electrodes. Thus, the mean-square deviation is not over 20 per cent. The maximum difference between the calculated and simulated eigenfrequencies in the drive channel of 11 SES prototypes is not over 3 per cent. The same difference is detected for eigenfrequencies in the first sensing channel of 17 SES prototypes.

This study shows a way to design and optimize the structure and theoretical background for the development of the MEMS inertial module combining the functions of gyroscope and accelerometer. The obtained results will improve and expand the manufacturing technology of MEMS gyroscopes and accelerometers.

A high-precision gyroscope is an important tool for accurate positioning, and the amplitude stability and frequency tracking ability of the drive control system are important and necessary conditions to ensure the precision of micro-electro-mechanical systems (MEMS) gyroscopes. To improve the precision of MEMS gyroscopes, this paper proposes a method to improve the amplitude stability and frequency tracking ability of a drive control system.

A frequency tracking loop and an amplitude control loop are proposed to improve the frequency tracking ability and amplitude stability of the drive control system for a MEMS gyroscopes. The frequency tracking loop mainly includes a phase detector, a frequency detector and a loop filter. And, the amplitude control loop mainly includes an amplitude detector, a low-pass filter and an amplitude control module. The simulation studies on the frequency tracking loop, amplitude control loop and drive control system composed of these two loops are implemented. The corresponding digital drive control algorithm is realized by the Verilog hardware description language, which is downloaded to the application-specific integrated circuits (ASIC) platform to verify the performances of the proposed method.

The simulation experiments in Matlab/Simulink and tests on the ASIC platform verify that the designed drive control system can keep the amplitude stable and track the driving frequency in real time with high precision.

This study shows a way to design and realize a drive control system for MEMS gyroscopes to improve their tracking ability. It is helpful for improving the precision of MEMS gyroscopes.

To reduce the influence of temperature on MEMS gyroscope, this paper aims to propose a temperature drift compensation method based on variational modal decomposition (VMD), time-frequency peak filter (TFPF), mind evolutionary algorithm (MEA) and BP neural network.

First, VMD decomposes gyro’s temperature drift sequence to obtain multiple intrinsic mode functions (IMF) with different center frequencies and then Sample entropy calculates, according to the complexity of the signals, they are divided into three categories, namely, noise signals, mixed signals and temperature drift signals. Then, TFPF denoises the mixed-signal, the noise signal is directly removed and the denoised sub-sequence is reconstructed, which is used as training data to train the MEA optimized BP to obtain a temperature drift compensation model. Finally, the gyro’s temperature characteristic sequence is processed by the trained model.

The experimental result proved the superiority of this method, the bias stability value of the compensation signal is 1.279 × 10^–3°/h and the angular velocity random walk value is 2.132 × 10^–5°/h/vHz, which is improved compared to the 3.361°/h and 1.673 × 10^–2°/h/vHz of the original output signal of the gyro.

This study proposes a multi-dimensional processing method, which treats different noises separately, effectively protects the low-frequency characteristics and provides a high-precision training set for drift modeling. TFPF can be optimized by SEVMD parallel processing in reducing noise and retaining static characteristics, MEA algorithm can search for better threshold and connection weight of BP network and improve the model’s compensation effect.

The selection of a suitable inertial measurement unit (IMU) is a critical step in an inertial navigation system (INS) design. Nevertheless, inertial sensors manufacturers are unwilling to publish their products’ accurate performance parameters along with a price. This paper aims to summarise the current IMU market review and point out parameters important for short-term inertial navigation.

The market review is based on the information published by manufacturers in brochures, datasheets and websites. Some information, including price, was also collected from sensors distributors. The entire collection of data includes data of over 150 sensors from 32 manufacturers and is valid for the first half of the year 2020.

This paper answers the following questions: •Why and where use inertial navigation? •Which parameters should one emphasise during IMU selection?•What is currently available on the IMU market? •Which parameters have a significant influence on price? •What are the advantages of specific sensor technology?

This paper gathers data published by IMU manufacturers, allowing for a quick overview of the current market. Based on real data, different sensor technologies are compared. The performed analysis presents the statistical basis for the IMU selection. By theoretical considerations a significance of sensor parameters is drawn and an approach to an IMU selection based on limited number of parameters is proposed. Although the considerations have been carried out regarding inertial navigation, the results from an extensive analysis of commercially available sensors may also be useful for other applications.

The purpose of this paper is to provide a technical review of silicon micro‐electromechanical systems (MEMS) technology and its applications.

Following an introduction, the paper describes silicon MEMS fabrication and assembly techniques, considers a selection of commercially important products and their applications and concludes with a brief review of power MEMS research.

Silicon MEMS fabrication technology is derived from techniques used in semiconductor manufacture and has yielded a diverse and ever‐growing range of sensors, actuators and other miniaturised devices that find applications in a multitude of industries.

This paper provides a detailed technical review of MEMS technology and its applications.

This study aims to design a new low-cost localization platform for estimating the location and orientation of a pedestrian in a building. The micro-electro-mechanical systems (MEMS) sensor error compensation and the algorithm were improved to realize the localization and altitude accuracy.

The platform hardware was designed with common low-performance and inexpensive MEMS sensors, and with a barometric altimeter employed to augment altitude measurement. The inertial navigation system (INS) – extended Kalman filter (EKF) – zero-velocity updating (ZUPT) (INS-EKF-ZUPT [IEZ])-extended methods and pedestrian dead reckoning (PDR) (IEZ + PDR) algorithm were modified and improved with altitude determined by acceleration integration height and pressure altitude. The “AND” logic with acceleration and angular rate data were presented to update the stance phases.

The new platform was tested in real three-dimensional (3D) in-building scenarios, achieved with position errors below 0.5 m for 50-m-long route in corridor and below 0.1 m on stairs. The algorithm is robust enough for both the walking motion and the fast dynamic motion.

The paper presents a new self-developed, integrated platform. The IEZ-extended methods, the modified PDR (IEZ + PDR) algorithm and “AND” logic with acceleration and angular rate data can improve the high localization and altitude accuracy. It is a great support for the increasing 3D location demand in indoor cases for universal application with ordinary sensors.

The purpose of this study is to explore a signal processing method to improve the angular rate accuracy of micro-electro-mechanical system (MEMS) gyroscope by combining numerous gyroscopes.

To improve the dynamic performance of the signal processing method, the interacting multiple model (IMM) can be applied to the fusion of gyroscope array. However, the standard IMM has constant Markov parameter, which may reduce the model switching speed. To overcome this problem, an adaptive IMM filter is developed based on the kurtosis of the gyroscope output, in which the transition probabilities are adjusted online by utilizing the dynamic information of the rate signal.

The experimental results indicate that the precision of the gyroscope array composed of six gyroscopes increases significantly and the kurtosis-based adaptive Markov parameter IMM filter (K-IMM) performs better than the baseline methods, especially under dynamic conditions. These experiments prove the validity of the proposed fusion method.

The proposed method can improve the accuracy of MEMS gyroscopes without breakthrough on hardware, which is necessary to extend their utility while not restricting the overwhelming advantages.

A K-IMM algorithm is proposed in this paper, which is used to improve the angular rate accuracy of MEMS gyroscope by combining numerous gyroscopes.

To describe the operation and historical development of MEMS gyroscopes and to consider their prospects in emerging high volume consumer markets.

This paper firstly describes the Coriolis effect and its application to MEMS‐based resonating gyroscopes. Designs are discussed and manufacturers identified. Applications and the prospects for MEMS gyroscopes in emerging, high volume markets are considered. Reference is made to a venture‐financed American start‐up who has targeted this sector.

This shows that technologically sophisticated MEMS gyroscopes are now in volume production and that prices are falling to a point where they may compete with accelerometers in the rapidly developing consumer markets.

This paper describes the principles and evolution of MEMS gyroscopes and identifies critical emerging markets.