MEMS Gyroscopes for Consumers and Industrial Applications

none2mixedAntonello, Riccardo; Oboe, RobertoAntonello, Riccardo; Oboe, Robert

Advanced interface systems for readout, control, and self-calibration of MEMS resonant gyroscopes

MEMS gyroscopes have become an essential component in consumer, industrial and automotive applications, owing to their small form factor and low production cost. However, their poor stability, also known as drift, has hindered their penetration into high-end tactical and navigation applications, where highly stable bias and scale factor are required over long period of time to avoid significant positioning error. Improving the long-term stability of MEMS gyroscopes has created new challenges in both the physical sensor design and fabrication, as well as the system architecture used for interfacing with the physical sensor. The objective of this research is to develop interface circuits and systems for in-situ control and self-calibration of MEMS resonators and resonant gyroscopes to enhance the stability of bias and scale factor without the need for any mechanical rotary stage, or expensive bulky lab characterization equipment. The self-calibration techniques developed in this work provide 1-2 orders of magnitude improvement in the drift of bias and scale factor of a resonant gyroscope over temperature and time.Ph.D

CMOS systems and circuits for sub-degree per hour MEMS gyroscopes

The objective of our research is to develop system architectures and CMOS circuits that interface with high-Q silicon microgyroscopes to implement navigation-grade angular rate sensors. The MEMS sensor used in this work is an in-plane bulk-micromachined mode-matched tuning fork gyroscope (M² – TFG ), fabricated on silicon-on-insulator substrate. The use of CMOS transimpedance amplifiers (TIA) as front-ends in high-Q MEMS resonant sensors is explored. A T-network TIA is proposed as the front-end for resonant capacitive detection. The T-TIA provides on-chip transimpedance gains of 25MΩ, has a measured capacitive resolution of 0.02aF /√Hz at 15kHz, a dynamic range of 104dB in a bandwidth of 10Hz and consumes 400μW of power. A second contribution is the development of an automated scheme to adaptively bias the mechanical structure, such that the sensor is operated in the mode-matched condition. Mode-matching leverages the inherently high quality factors of the microgyroscope, resulting in significant improvement in the Brownian noise floor, electronic noise, sensitivity and bias drift of the microsensor. We developed a novel architecture that utilizes the often ignored residual quadrature error in a gyroscope to achieve and maintain perfect mode-matching (i.e.0Hz split between the drive and sense mode frequencies), as well as electronically control the sensor bandwidth. A CMOS implementation is developed that allows mode-matching of the drive and sense frequencies of a gyroscope at a fraction of the time taken by current state of-the-art techniques. Further, this mode-matching technique allows for maintaining a controlled separation between the drive and sense resonant frequencies, providing a means of increasing sensor bandwidth and dynamic range. The mode-matching CMOS IC, implemented in a 0.5μm 2P3M process, and control algorithm have been interfaced with a 60μm thick M2−TFG to implement an angular rate sensor with bias drift as low as 0.1°/hr ℃ the lowest recorded to date for a silicon MEMS gyro.Ph.D.Committee Chair: Farrokh Ayazi; Committee Member: Jennifer Michaels; Committee Member: Levent Degertekin; Committee Member: Paul Hasler; Committee Member: W. Marshall Leac

Design and Characterization of a Low Cost MEMS IMU Cluster for Precision Navigation

The fast paced development of micro-electromechanical systems (MEMS) technology in recent years has resulted in the availability of low cost gyroscopes and accelerometers in commercial markets. These sensors can be integrated into a single device known as an inertial measurement unit (IMU). An IMU is capable of tracking and navigating a vehicle for a short period of time in the absence of external position and attitude updates. The precision of the manufacturing techniques used to fabricate commercial MEMS sensors as well as their mechanical nature result in noise and errors that limit their performance. It has been mathematically shown that combining many MEMS sensors into a single device results in improved performance characteristics which are unattainable using a single MEMS sensor. The primary aim of this thesis is to design and validate the performance of a prototype IMU composed of a cluster of individual MEMS IMUs. The secondary aim of this thesis is to derive and validate a set of computationally inexpensive coning and sculling algorithms to mitigate dead-reckoning errors resulting from high frequency motion of the vehicle

Development of dynamic model and control techniques for microelectromechanical gyroscopes

In this thesis we investigate the effects of stiffness, damping and temperature on the performance of a MEMS vibratory gyroscope. The stiffness and damping parameters are chosen because they can be appropriately designed to synchronize the drive and sense mode resonance to enhance the sensitivity and stability of MEMS gyroscope. Our results show that increasing the drive axis stiffness from its tuned value by 50%, reduces the sense mode magnitude by ~27% and augments the resonance frequency by ~21%. The stiffness and damping are mildly sensitive to typical variations in operating temperature. The stiffness decreases by 0.30%, while the damping increases by 3.81% from their initial values, when the temperature is raised from -40 to 60C. Doubling the drive mode damping from its tuned value reduces the oscillation magnitude by 10%, but ~0.20% change in the resonance frequency. The predicted effects of stiffness, damping and temperature can be utilized to design a gyroscope for the desired operating condition

Degree-per-hour mode-matched micromachined silicon vibratory gyroscopes

The objective of this research dissertation is to design and implement two novel micromachined silicon vibratory gyroscopes, which attempt to incorporate all the necessary attributes of sub-deg/hr noise performance requirements in a single framework: large resonant mass, high drive-mode oscillation amplitudes, large device capacitance (coupled with optimized electronics), and high-Q resonant mode-matched operation. Mode-matching leverages the high-Q (mechanical gain) of the operating modes of the gyroscope and offers significant improvements in mechanical and electronic noise floor, sensitivity, and bias stability. The first micromachined silicon vibratory gyroscope presented in this work is the resonating star gyroscope (RSG): a novel Class-II shell-type structure which utilizes degenerate flexural modes. After an iterative cycle of design optimization, an RSG prototype was implemented using a multiple-shell approach on (111) SOI substrate. Experimental data indicates sub-5 deg/hr Allan deviation bias instability operating under a mode-matched operating Q of 30,000 at 23ºC (in vacuum). The second micromachined silicon vibratory gyroscope presented in this work is the mode-matched tuning fork gyroscope (M2-TFG): a novel Class-I tuning fork structure which utilizes in-plane non-degenerate resonant flexural modes. Operated under vacuum, the M2-TFG represents the first reported high-Q perfectly mode-matched operation in Class-I vibratory microgyroscope. Experimental results of device implemented on (100) SOI substrate demonstrates sub-deg/hr Allan deviation bias instability operating under a mode-matched operating Q of 50,000 at 23ºC. In an effort to increase capacitive aspect ratio, a new fabrication technology was developed that involved the selective deposition of doped-polysilicon inside the capacitive sensing gaps (SPD Process). By preserving the structural composition integrity of the flexural springs, it is possible to accurately predict the operating-mode frequencies while maintaining high-Q operation. Preliminary characterization of vacuum-packaged prototypes was performed. Initial results demonstrated high-Q mode-matched operation, excellent thermal stability, and sub-deg/hr Allan variance bias instability.Ph.D.Committee Chair: Dr. Farrokh Ayazi; Committee Member: Dr. Mark G. Allen; Committee Member: Dr. Oliver Brand; Committee Member: Dr. Paul A. Kohl; Committee Member: Dr. Thomas E. Michael

Estimating Epipolar Geometry With The Use of a Camera Mounted Orientation Sensor

Context: Image processing and computer vision are rapidly becoming more and more commonplace, and the amount of information about a scene, such as 3D geometry, that can be obtained from an image, or multiple images of the scene is steadily increasing due to increasing resolutions and availability of imaging sensors, and an active research community. In parallel, advances in hardware design and manufacturing are allowing for devices such as gyroscopes, accelerometers and magnetometers and GPS receivers to be included alongside imaging devices at a consumer level. Aims: This work aims to investigate the use of orientation sensors in the field of computer vision as sources of data to aid with image processing and the determination of a scene’s geometry, in particular, the epipolar geometry of a pair of images - and devises a hybrid methodology from two sets of previous works in order to exploit the information available from orientation sensors alongside data gathered from image processing techniques. Method: A readily available consumer-level orientation sensor was used alongside a digital camera to capture images of a set of scenes and record the orientation of the camera. The fundamental matrix of these pairs of images was calculated using a variety of techniques - both incorporating data from the orientation sensor and excluding its use Results: Some methodologies could not produce an acceptable result for the Fundamental Matrix on certain image pairs, however, a method described in the literature that used an orientation sensor always produced a result - however in cases where the hybrid or purely computer vision methods also produced a result - this was found to be the least accurate. Conclusion: Results from this work show that the use of an orientation sensor to capture information alongside an imaging device can be used to improve both the accuracy and reliability of calculations of the scene’s geometry - however noise from the orientation sensor can limit this accuracy and further research would be needed to determine the magnitude of this problem and methods of mitigation

Innovative Solutions for Navigation and Mission Management of Unmanned Aircraft Systems

The last decades have witnessed a significant increase in Unmanned Aircraft Systems (UAS) of all shapes and sizes. UAS are finding many new applications in supporting several human activities, offering solutions to many dirty, dull, and dangerous missions, carried out by military and civilian users. However, limited access to the airspace is the principal barrier to the realization of the full potential that can be derived from UAS capabilities. The aim of this thesis is to support the safe integration of UAS operations, taking into account both the user's requirements and flight regulations. The main technical and operational issues, considered among the principal inhibitors to the integration and wide-spread acceptance of UAS, are identified and two solutions for safe UAS operations are proposed: A. Improving navigation performance of UAS by exploiting low-cost sensors. To enhance the performance of the low-cost and light-weight integrated navigation system based on Global Navigation Satellite System (GNSS) and Micro Electro-Mechanical Systems (MEMS) inertial sensors, an efficient calibration method for MEMS inertial sensors is required. Two solutions are proposed: 1) The innovative Thermal Compensated Zero Velocity Update (TCZUPT) filter, which embeds the compensation of thermal effect on bias in the filter itself and uses Back-Propagation Neural Networks to build the calibration function. Experimental results show that the TCZUPT filter is faster than the traditional ZUPT filter in mapping significant bias variations and presents better performance in the overall testing period. Moreover, no calibration pre-processing stage is required to keep measurement drift under control, improving the accuracy, reliability, and maintainability of the processing software; 2) A redundant configuration of consumer grade inertial sensors to obtain a self-calibration of typical inertial sensors biases. The result is a significant reduction of uncertainty in attitude determination. In conclusion, both methods improve dead-reckoning performance for handling intermittent GNSS coverage. B. Proposing novel solutions for mission management to support the Unmanned Traffic Management (UTM) system in monitoring and coordinating the operations of a large number of UAS. Two solutions are proposed: 1) A trajectory prediction tool for small UAS, based on Learning Vector Quantization (LVQ) Neural Networks. By exploiting flight data collected when the UAS executes a pre-assigned flight path, the tool is able to predict the time taken to fly generic trajectory elements. Moreover, being self-adaptive in constructing a mathematical model, LVQ Neural Networks allow creating different models for the different UAS types in several environmental conditions; 2) A software tool aimed at supporting standardized procedures for decision-making process to identify UAS/payload configurations suitable for any type of mission that can be authorized standing flight regulations. The proposed methods improve the management and safe operation of large-scale UAS missions, speeding up the flight authorization process by the UTM system and supporting the increasing level of autonomy in UAS operations

Python-based MEMS inertial sensors design, simulation and optimization

With the rapid growth in microsensor technology, a never-ending range of possible applications emerged. The developments in fabrication techniques gave room to the creation of numerous new products that significantly improve human life. However, the evolution in the design, simulation, and optimization process of these devices did not observe a similar rapid growth. Thus, the microsensor technology would benefit from significant improvements in this domain. This work presents a novel methodology for electro-mechanical co optimization of microelectromechanical systems (MEMS) inertial sensors. The developed software tool comprises geometry design, finite element method (FEM) analysis, damping calculation, electronic domain simulation, and a genetic algorithm (GA) optimization process. It allows for a facilitated system-level MEMS design flow, in which electrical and mechanical domains communicate with each other to achieve an optimized system performance. To demonstrate the efficacy of the co-optimization methodology, an open-loop capacitive MEMS accelerometer and an open-loop Coriolis vibratory MEMS gyroscope were simulated and optimized - these devices saw a sensitivity improvement of 193.77% and 420.9%, respectively, in comparison to its original state

Development and implementation of automated interferometric microscope for study of MEMS inertial sensors

Microelectromechanical systems (MEMS) are quickly becoming ubiquitous in commercial and military applications. As the use of such devices increases their reliability becomes of great importance. Although there has been significant research in the areas of MEMS errors, there is a lack of work regarding long term reliability of packaged systems. Residual thermomechanical stresses might relax over time which affects physical distances within a package, ultimately influencing the performance of a device. One reason that there has not been sufficient work performed on the long-term effects on structures might be the lack of a tool capable of characterizing the effects. MEMS devices have been measured for shape and its changes using interferometric techniques for some time now. Commercially available systems are able to make high resolution measurements, however they might lack loading options. To study aging effects on components a test might need to run continuously for days or weeks, with systematic operations performed throughout the process. Such a procedure is conducive to an automated data acquisition system. A system has been developed at WPI using a Twyman-Green interferometer and a custom software suite. The abilities of this system are demonstrated through analysis performed on MEMS tuning fork gyroscope (TFG) sensors. Specifically, shape is recorded to investigate die bond relaxation as a function of time and thermal cycle. Also presented are measurements made using stroboscopic illumination on operating gyroscopes, in situ. The effect of temperature on the performance of the sensors is investigated using a customized precision rate table