Weizheng Yuan

A Handheld Inertial Pedestrian Navigation System With Accurate Step Modes and Device Poses Recognition

In this paper, a handheld inertial pedestrian navigation system (IPNS) based on low-cost microelectromechanical system sensors is presented. Using the machine learning method of support vector machine, a multiple classifier is developed to recognize human step modes and device poses. The accuracy of the selected classifier is >85%. A novel step detection model is created based on the results of the classifier to eliminate the over-counting and under-counting errors. The accuracy of the presented step detector is >98%. Based on the improvements of the step modes recognition and step detection, the IPNS realized precise tracking using the pedestrian dead reckoning algorithm. The largest location error of the IPNS prototype is ~40 m in an urban area with a 2100-m-long distance.

Superhydrophobic silicon surfaces with micro–nano hierarchical structures via deep reactive ion etching and galvanic etching

An effective fabrication method combining deep reactive ion etching and galvanic etching for silicon micro-nano hierarchical structures is presented in this paper. The method can partially control the morphology of the nanostructures and enables us to investigate the effects of geometry changes on the properties of the surfaces. The forming mechanism of silicon nanostructures based on silver nanoparticle galvanic etching was illustrated and the effects of process parameters on the surface morphology were thoroughly discussed. It is found that process parameters have more impact on the height of silicon nanostructure than its diameter. Contact angle measurement and tilting/dropping test results show that as-prepared silicon surfaces with hierarchical structures were superhydrophobic. Whats more, two-scale model composed of micropillar arrays and nanopillar arrays was proposed to study the wettability of the surface with hierarchical structures. Wettability analysis results indicate that the superhydrophobic surface may demonstrate a hybrid state at which water sits on nanoscale pillars and immerses into microscale grooves partially.

A Micro Nuclear Battery Based on SiC Schottky Barrier Diode

Based on the betavoltaic and alphavoltaic effects, a 4H-SiC micronuclear battery was demonstrated. A Schottky barrier diode, in place of the previously used p-n junction diode, was utilized for carrier separation. A theoretical model was derived to predict the output electrical power. Using beta radioisotope 63Ni and alpha radioisotope 241Am as the radiation sources, the micro nuclear battery was tested and proved to be effective to transfer decay energy into electrical power. The experimental results show that the theoretical model can basically predict the performance of the micronuclear battery. Although the energy conversion efficiencies under illumination of 63Ni and 241Am are only 0.5% and 0.1% at current status, an improvement by an order of magnitude can be expected if the doping concentration of the epilayer can be decreased to the optimal value.

An Acceleration Sensing Method Based on the Mode Localization of Weakly Coupled Resonators

This paper reports an acceleration sensing method based on two weakly coupled resonators (WCRs) using the phenomenon of mode localization. When acceleration acts on the proof masses, differential electrostatic stiffness perturbations will be applied to the WCRs, leading to mode localization, and thus, mode shape changes. Therefore, acceleration can be sensed by measuring the amplitude ratio shift. The proposed mode localization with the differential perturbation method leads to a sensitivity enhancement of a factor of 2 than the common single perturbation method. The theoretical model of the sensitivity, bandwidth, and linearity of the accelerometer is established and verified. The measured relative shift in amplitude ratio (~312162 ppm/g) is 302 times higher than the shift in resonance frequency (~1035 ppm/g) within the measurement range of ±1 g. The measured resolution based on the amplitude ratio is 0.619 mg and the nonlinearity is ~3.5% in the open-loop measurement operation.

Signal Processing of MEMS Gyroscope Arrays to Improve Accuracy Using a 1st Order Markov for Rate Signal Modeling

This paper presents a signal processing technique to improve angular rate accuracy of the gyroscope by combining the outputs of an array of MEMS gyroscope. A mathematical model for the accuracy improvement was described and a Kalman filter (KF) was designed to obtain optimal rate estimates. Especially, the rate signal was modeled by a first-order Markov process instead of a random walk to improve overall performance. The accuracy of the combined rate signal and affecting factors were analyzed using a steady-state covariance. A system comprising a six-gyroscope array was developed to test the presented KF. Experimental tests proved that the presented model was effective at improving the gyroscope accuracy. The experimental results indicated that six identical gyroscopes with an ARW noise of 6.2 °/√h and a bias drift of 54.14 °/h could be combined into a rate signal with an ARW noise of 1.8 °/√h and a bias drift of 16.3 °/h, while the estimated rate signal by the random walk model has an ARW noise of 2.4 °/√h and a bias drift of 20.6 °/h. It revealed that both models could improve the angular rate accuracy and have a similar performance in static condition. In dynamic condition, the test results showed that the first-order Markov process model could reduce the dynamic errors 20% more than the random walk model.

Combining Numerous Uncorrelated MEMS Gyroscopes for Accuracy Improvement Based on an Optimal Kalman Filter

In this paper, an approach to improve the accuracy of microelectromechanical systems (MEMS) gyroscopes by combining numerous uncorrelated gyroscopes is presented. A Kalman filter (KF) is used to fuse the output signals of several uncorrelated sensors. The relationship between the KF bandwidth and the angular rate input is quantitatively analyzed. A linear model is developed to choose suitable system parameters for a dynamic application of the concept. Simulation and experimental tests of a six-gyroscope array proved that the presented approach was effective to improve the MEMS gyroscope accuracy. The experimental results indicate that six identical gyroscopes with a noise density of 0.11°/s/√Hz and a bias instability of 62°/h can be combined to form a virtual gyroscope with a noise density of 0.03°/s/√Hz and a bias instability of 16.8°/h . The accuracy improvement is better than that of a simple averaging process of the individual sensors.

Integrated Behavior Simulation and Verification for a MEMS Vibratory Gyroscope Using Parametric Model Order Reduction

In this paper, a parameterized reduced model of a vibratory microelectromechanical systems (MEMS) gyroscope is established using a parametric model order reduction algorithm. In the reduction process, not only the input angular velocity, material density, Youngs modulus, and Rayleigh damping coefficient but also the coefficient of thermal expansion and the change in temperature were all preserved. Based on this model, the integrated behavior simulation of the MEMS gyroscope, including many environmental factors in engineering situations, was performed in an accurate and fast way. Compared with the finite-element method, the relative error of the reduced-order model was less than 4.2%, while the computational efficiency was improved about five times. The cosimulation with a complete interface circuit was successfully performed in a very fast way, which provides a convenient platform for designers to evaluate the performance of sensors. The experimental verification proves that the reduced model can provide a reliable simulation result, although some errors exist.

Design and optimization of a micro piezoresistive pressure sensor

This paper focuses the structural design and optimisation of the micro piezoresistive pressure sensor to enhance the sensitivity and linearity. Finite element method (FEM) is adopted to optimize the sensor parameters, such as the resistor location and number of turns. An absolutely type pressure sensor with 150kPa full scale span (FSS) is built based on the optimal design programme as well as the bulk- micromachined process. For an 1150-mum-wide 30-mum-thick square-shape pressure sensor, experimental results show that the sensitivity of 2.3mV/V/10kPa, linearity error of 0.57% FSS and pressure hysteresis of 0.04% FSS are achieved. The well compatibility between the results of simulation and testing certifies the validity of the optimized scheme.

Theoretical Modeling for a Six-DOF Vortex Inertial Sensor and Experimental Verification

This paper reports on a multi-axis fluidic inertial sensor that can detect three components of angular rate and linear acceleration. The sensor uses a vortex gas flow instead of the traditional linear gas flow as the inertial mass to detect the angular rate and linear acceleration. For this complex multi-axis sensing scheme, the theoretical modeling for the sensitivity and the cross-axis sensitivity of the sensor are discussed in detail. During the verification of the sensors performance, the vortex was created by jetting the air supplied by an external air pump into a detection chamber via two opposing nozzle orifices in opposite directions. A configuration of microfabricated thermistors was constructed to realize multi-axis detection. The measured sensitivities of the gyroscope for the x-axis, y-axis, and z-axis were 0.429, 0.338, and 0.159 mV/°/s, respectively. The measured sensitivities of the accelerometer for the x-axis, y-axis, and z-axis were 0.185, 0.180, and 0.133 V/g, respectively. The results prove that the vortex sensor can effectively detect six-degree-of-freedom spatial motion.

A Micromachined Pressure Sensor with Integrated Resonator Operating at Atmospheric Pressure

A novel resonant pressure sensor with an improved micromechanical double-ended tuning fork resonator packaged in dry air at atmospheric pressure is presented. The resonator is electrostatically driven and capacitively detected, and the sensor is designed to realize a low cost resonant pressure sensor with medium accuracy. Various damping mechanisms in a resonator that is vibrating at atmospheric pressure are analyzed in detail, and a formula is developed to predict the overall quality factor. A trade-off has been reached between the quality factor, stress sensitivity and drive capability of the resonator. Furthermore, differential sense elements and the method of electromechanical amplitude modulation are used for capacitive detection to obtain a large signal-to-noise ratio. The prototype sensor chip is successfully fabricated using a micromachining process based on a commercially available silicon-on-insulator wafer and is hermetically encapsulated in a custom 16-pin Kovar package. Preliminary measurements show that the fundamental frequency of the resonant pressure sensor is approximately 34.55 kHz with a pressure sensitivity of 20.77 Hz/kPa. Over the full scale pressure range of 100–400 kPa and the whole temperature range of −20–60 °C, high quality factors from 1,146 to 1,772 are obtained. The characterization of the prototype sensor reveals the feasibility of a resonant pressure sensor packaged at atmospheric pressure.