三轴数字MEMS加速度计现场标定方法

微机电系统(micro electro mechanical systems,简称MEMS)加速度传感器作为低成本惯性测量单元在物体姿态监测中有着广泛应用。根据三轴数字加速度传感器的输出数学模型,详细推导了如何计算数学模型中标度因数、安装误差系数以及零偏值。提出一种基于长方体的六位置简单标定方法,对比三轴转台精确标定结果表明六位置简单标定法简单易行,精度较高,易于单片机实现,适合不具备三轴转台的场所,且该方法对MEMS三轴数字加速度计的校准具有很好的通用性。     

Capacitive MEMS accelerometers for measuring high-g accelerations

A possibility of creating a capacitive accelerometer for measuring high-g accelerations (up to 10⁶ g and higher) is discussed. It is demonstrated that insertion of a thin electret film with a high surface potential into the gap between the electrodes ensures significant expansion of the frequency and amplitude ranges of acceleration measurements, whereas the size of the proposed device is smaller than that of available MEMS accelerometers for measuring high-g accelerations. A mathematical model of an electret accelerometer for high-g accelerations is developed, and the main specific features of accelerometer operation are analyzed.     

卡尔曼滤波在MEMS惯性姿态测量中的应用

由于测控成本和有效载荷的限制,一般采用微机电系统(MEMS)惯性传感器来测量小型无人机的飞行姿态。在MC9S12XS128单片机上通过嵌入式软件编程实现了卡尔曼滤波算法,并在JZJ-1型自准直仪转台上对MEMS加速度计和陀螺仪的输出信号进行了数据融合试验,较好地解决了MEMS惯性测量系统的零漂和机械振动干扰问题。     

Strapdown gyrocompass algorithm for AUV attitude determination using a digital filter

The strapdown gyrocompass can provide attitude by measuring the Earth’s gravity vector. In practical applications, there usually exists unwanted disturbance accelerometers that will distort the accelerometer measurements, hence a filtering out procedure is essential. Current attitude determination method based on pendulum cutting off technology has the limitation for vehicle moving mode. This paper proposes a new strapdown gyrocompass algorithm via processing the accelerometer measurement with Butterworth low-pass filter (LPF) to remove the high frequency dynamic disturbance components. When the gravity variation in inertial frame is regulated, LPF can be applied to properly get the gravity even in the presence of acceleration disturbances, and subsequently can be applied to calculate the strapdown gyrocompass attitude. The proposed algorithm does not require declination information and inertial element biases estimation. The field test has been conducted and the results verified the effectiveness and reliability of the proposed AUV attitude determination method and have also shown that the gravity is proportional to the latitude and altitude of AUV.     

力反馈微加速度计的准静态和阶跃响应模型

对于微机械电容式加速度计,为了检测微小电容变化,必须引入交直流电压驱动信号,然而该静电力的存在显著影响传感器的最大可靠工作范围。对准静态惯性信号和阶跃惯性信号,深入研究了力反馈加速度计的可靠工作范围,建立了不同偏压配置的驱动信号对引起吸合失效的临界加速度信号的影响模型。研究结果表明静电力对阶跃信号的影响要比准静态信号大,动态工作条件下所能承受的最大阶跃加速度信号比准静态信号要小一个数量因子。对于双边驱动的力反馈加速度计,正正偏压配置或正负偏压配置可以最大程度地减小驱动信号引起的传感器吸合失效,从而增大可靠工作范围;而负负偏压配置或负正偏压配置增大了驱动信号效应,从而大大减小了可靠工作范围。     

Characterization and calibration of MEMS inertial sensors for state and parameter estimation applications

Widening applications of inertial sensors have triggered the search for cost effective sensors and those based on MEMS technology have been gaining popularity and widespread use particularly for lower cost applications. However, inertial sensors are subject to various error sources and characteristics of these should be modelled carefully. Corrective calibration is required for successful use for anything but the most trivial applications, body state estimation and navigation being important application areas. In this paper, we review the deterministic error and random noise sources for these sensors, consider a number of inertial sensor calibration tests to provide models for these errors and derive the calibration parameters for MEMS based strapdown IMUs. We carry out these tests and present the results for a low cost and popular IMU. We further provide performance results for an example application of body state and parameter estimation using the derived calibration data and discuss our results.     

面向INS数据分类的鲁棒性无监督聚类方法

针对惯性导航系统(INS)中加速度计、陀螺仪测量误差随时间积累的问题,提出了一种基于内核模糊C均值的无监督广度优先搜索聚类算法(RUCM),用于INS模块采集数据的去噪及其运动阶段的分类划分。RUCM通过广度优先搜索方法遍历相邻的数据,使用阈值确定聚类数目,同时引入高斯核函数提高RUCM对噪声和异常点干扰的鲁棒性,并验证了其收敛性和鲁棒性。最后,在基于MEMS的INS模块实物系统中验证了该算法,结果表明所提出的方法能够提高随机采样INS数据的聚类性能,抑制了噪声干扰,使其INS运动阶段的聚类划分更加清晰与明确。     

Optimization of multilayer cylindrical coils in a wireless localization system to track a capsule-shaped micro-device

A wireless electromagnetic localization method has been presented to track capsule-shaped micro-devices in the gastrointestinal tract. And a prototype for the novel localization system has been developed. In the localization method, cylindrical coils placed on the patient’s abdomen generate alternating electromagnetic fields one by one. The system of equations from the localization model has been established and then transformed into a nonlinear optimization problem. The localization method presents excellent anti-interference ability and high stability. In order to solve the magnetic inverse problem in the localization model, an analytical expression between the magnetic flux density and the position & orientation should be derived by superposition of the fields generated by the coil turns, which causes systematic errors. As a result, the geometry of the cylindrical coils is optimized to reduce the errors. A full factorial experiment with two factors has been carried out. The experiment shows that the optimal L/Dout ratio and Din/Dout ratio are 0.4 and 0.8, respectively. In this case, the mean error and the standard deviation are reduced to 0.89% and 0.77%, respectively, where the distance along the axis of the cylindrical coil from the coil’s center to a measured point is 30 mm. Furthermore, the experimental results also show that the imitation error decreases significantly with increased distance from the coil. The accuracy of the localization model can be further improved using the optimized coil.     

High accuracy navigation information estimation for inertial system using the multi-model EKF fusing adams explicit formula applied to underwater gliders

The underwater navigation system, mainly consisting of MEMS inertial sensors, is a key technology for the wide application of underwater gliders and plays an important role in achieving high accuracy navigation and positioning for a long time of period. However, the navigation errors will accumulate over time because of the inherent errors of inertial sensors, especially for MEMS grade IMU (Inertial Measurement Unit) generally used in gliders. The dead reckoning module is added to compensate the errors. In the complicated underwater environment, the performance of MEMS sensors is degraded sharply and the errors will become much larger. It is difficult to establish the accurate and fixed error model for the inertial sensor. Therefore, it is very hard to improve the accuracy of navigation information calculated by sensors. In order to solve the problem mentioned, the more suitable filter which integrates the multi-model method with an EKF approach can be designed according to different error models to give the optimal estimation for the state. The key parameters of error models can be used to determine the corresponding filter. The Adams explicit formula which has an advantage of high precision prediction is simultaneously fused into the above filter to achieve the much more improvement in attitudes estimation accuracy. The proposed algorithm has been proved through theory analyses and has been tested by both vehicle experiments and lake trials. Results show that the proposed method has better accuracy and effectiveness in terms of attitudes estimation compared with other methods mentioned in the paper for inertial navigation applied to underwater gliders.     

Modeling and compensation of MEMS gyroscope output data based on support vector machine

The modeling and compensation method of the angular rate error of MEMS gyro MG31-300, based on support vector machine, is described in this paper. Reference angular rates were generated by the single-axis rate turntable. The output data of MG31-300 under different input angular rates were collected and analyzed. Considering the nonlinear and random characteristics of the angular rate error, the support vector machine model is established, which uses the output voltage of gyro as the input and provides angular rate error as the output. The resolution of the angular rate error is improved by this modeling method. The result shows that the fitting error of the model was 0.0701°/s (1σ). Finally, within MG31-300 measuring range (−300°/s to 300°/s), some testing points besides the training samples were selected to testify and verify the model. The results indicate that, the support vector machine model has high precision and good generalization ability.     

Development of multiple performance indices and system parameter study for the design of a MEMS accelerometer

For the design of a MEMS accelerometer, proper performance indices should be defined and employed. Performance indices are obtained using either an experimental method or a numerical method. In the present study, a vibration analysis model of a MEMS accelerometer is introduced to calculate three performance indices: sensitivity, measurable acceleration range, and measurable frequency range. The accuracy of the vibration analysis model is first validated by comparing its modal and transient results with those of a commercial finite element code. Measurable acceleration and frequency ranges versus allowable errors for electrical and mechanical sensitivities are obtained and the effects of system parameter variations on the three performance indices are investigated.     

Distributed observers for pose estimation in the presence of inertial sensory soft faults

Distributed Particle-Kalman Filter based observers are designed in this paper for inertial sensors (gyroscope and accelerometer) soft faults (biases and drifts) and rigid body pose estimation. The observers fuse inertial sensors with Photogrammetric camera. Linear and angular accelerations as unknown inputs of velocity and attitude rate dynamics, respectively, along with sensory biases and drifts are modeled and augmented to the moving body state parameters. To reduce the complexity of the high dimensional and nonlinear model, the graph theoretic tearing technique (structural decomposition) is employed to decompose the system to smaller observable subsystems. Separate interacting observers are designed for the subsystems which are interacted through well-defined interfaces. Kalman Filters are employed for linear ones and a Modified Particle Filter for a nonlinear non-Gaussian subsystem which includes imperfect attitude rate dynamics is proposed. The main idea behind the proposed Modified Particle Filtering approach is to engage both system and measurement models in the particle generation process. Experimental results based on data from a 3D MEMS IMU and a 3D camera system are used to demonstrate the efficiency of the method.     

硅微振梁式加速度计的温度检测及闭环控制

为实现硅微振梁式加速度计系统芯片级温度测量及系统闭环,本文针对系统的非惯性结构部分提出了微机电系统（MEMS）结构温度的芯片级测量和闭环控制优化方法。与以温控罩的温度作为参考温度的方法不同,该方法提出了供芯片级温度测量的MEMS结构、工艺及配套电路,通过直接测量MEMS结构的温度完成实时补偿,从而提高了测量精度。该方法在闭环控制的前置电路中应用了二极管电容解调电路,与前期使用的跨阻或者跨导方案相比,对器件的要求从pA级降至nA级。运用时域方法求得二极管电路方案的解析解,提出参数优化设计方法,保证了电容测量输入与输出间的线性关系。最后,采用二阶最优模型对闭环控制的后置电路进行参数优化,控制了上电时间。配合硅微振梁式加速度计原理样机进行了实验。实验结果表明,温度补偿后的零偏稳定性为52.0 μg,标度因子稳定性为16.0×10^-6,分辨率为34.9 μg。这些结果验证了本文理论的可行性。     

捷联惯导系统误差模型与仿真分析

为研究捷联惯导系统短时间导航精度,建立了导航误差数学模型,分析了惯性器件误差对系统导航精度的影响。应用捷联惯性导航原理,针对系统短时间导航的特点,简化载体在导航坐标系的导航方程;由惯性器件安装误差与陀螺仪等效零漂经过方向余弦矩阵变换建立载体姿态误差方程;结合导航方程、姿态误差方程与惯性器件误差推导出载体速度误差与位置误差数学模型。在此基础上,建立了误差状态空间方程与误差模型框图。在Matlab/Simulink环境下建立了误差数学模型计算模块,用捷联惯导算法与误差模型共同解算地面150秒导航试验数据,结果表明：导航系X轴的相对系统误差小于20%,Y轴、Z轴的相对系统误差小于5%,验证了误差数学模型的正确性。此外,分析了加速度计精度的变化对短时间工作的捷联惯导系统导航误差产生基本的影响。     

机器视觉与惯性信息融合的轨道线形检测

轨道空间线形检测是保障列车运行安全的一项关键技术,受陀螺仪及加速度计的累计误差的影响,使得基于常规的惯性单元的轨道线形检测方法在低速连续运动测量下精度较低。为了解决该问题,提出一种基于机器视觉与惯性信息多传感器融合的轨道空间线形检测方法。通过分别建立惯性测量单元与机器视觉转换矩阵,倾角仪与惯性测量单元旋转矩阵及惯性测量单元与机器视觉平移关系矩阵,将动态测量数据转换到世界坐标系下,实现多传感器间的融合定标。利用扩展卡尔曼滤波将机器视觉与惯性信息进行融合,提高检测精度。最后,通过搭建测量平台进行实验验证,结果表明该方法的测量精度小于0.5mm且标准差低于0.3。与常规惯性测量方法相比,测量精度提高近10倍。     

一种有效的加速度计静态模型辨识方法

研究了惯性元器件加速度计静态模型参数的标定问题，首先给出了加速度计静态数学模型，并在此基础上研究了一种有效的加速度计标度因数，安装误差的标定方法，给出了具体的实验方法和数据处理方法，理论分析和实验试验表明所述方法能够有效地标定加速度计静态模型各项参数。     

考虑横向灵敏度的三轴加速度传感器标定方法研究

横向灵敏度是单轴加速度传感器的重要指标之一,它直接影响到三轴加速度传感器的标定模型与测量精度.本论文以三轴MEMS加速度传感器为研究对象,在传统的标定模型中引入了导致测量耦合的横向灵敏度误差,建立了一种新的三轴加速度传感器标定模型,该模型将传感器的横向灵敏度以对称矩阵的形式引入现有的标定公式,构建了包含零位偏差、标度因...     

Manufacturing yield and cost estimation of a MEMS accelerometer based on statistical uncertainty analysis

Manufacturing yield maximization to minimize the production cost is one of the most important objectives of manufacturing. The manufacturing yield is the probability to manufacture products that satisfy multiple performance requirements. For a given set of product performance requirements, its manufacturing yield can be estimated based on the system parameter uncertainties including manufacturing tolerances, which are related to the production cost. We employ three performance indices for the design of a MEMS accelerometer, and the manufacturing yield and cost are estimated using statistical uncertainty analysis methods. The effects of the MEMS accelerometer parameter uncertainties on the manufacturing yield and cost are investigated.     

不依赖精密转台的 MEMS-IMU 误差标定补偿方法

微机电惯性测量单元(MEMS-IMU)具有尺寸小、重量轻、成本低、可靠性高等优点,在机器人、虚拟现实以及智能穿戴等诸多领域广泛应用。低成本的微机电惯性测量单元在使用过程中受噪声和零偏误差等影响,需要通过测试和误差补偿手段来提高其实际使用精度。本文提出了一种全面测试和补偿惯性测量单元误差的方法,通过建立MEMS-IMU的误差模型,使用优化方法标定误差模型中的系统误差参数;使用Allan方差分析方法确定随机误差参数;基于上述结果,采用与视觉融合的非线性优化方法在线实时估计并补偿零偏,最终达到提高定位精度的目的。通过实验分析,上述组合方法不需要使用专门测试标定设备,能够有效补偿低成本微机电惯性测量单元的误差,提高定位精度。     

基于刚度轴偏角预估机制的 MEMS 多环谐振陀螺全闭环控制方法

针对微机电系统多环谐振陀螺正交闭环回路存在控制误差问题,提出一种基于刚度轴偏角预估机制的多环陀螺全闭环控制方法。该方法通过对微机电系统多环谐振陀螺刚度轴偏角预估,实现正交闭环回路参数自动优化调整。同时,提出了基于刚度轴偏角预估机制的全数字化闭环控制方法,实现微机电系统多环谐振陀螺的驱动、检测、正交、模态匹配环路的全闭环控制。该方法可提升正交闭环回路信噪比,增强陀螺正交漂移的抑制能力,降低陀螺零偏输出,改善陀螺的零偏不稳定性。实验结果表明,采用本文提出的基于刚度轴偏角预估机制的全闭环控制方法后,微机电系统多环谐振陀螺的零偏输出由0.201°/s降低为0.021 3°/s,零偏不稳定性由39.42°/h降低为1.237°/h,分别降低了9.44倍和31.86倍,验证了该方法对提升微机电系统多环谐振陀螺仪性能的有效性。