基于Kalman滤波的MEMS陀螺测量误差估计研究

针对微机械陀螺仪存在的测量精度较低的问题,本文采用Kalman滤波算法,对微机械陀螺仪在测量上存在的零位误差、标度因数误差、非线性平方敏感误差、加速度的敏感误差等进行了估计,建立了Kalman滤波的微机械陀螺仪测量误差估计模型,并采用Kalman滤波器对微机械陀螺仪的各项误差进行估计分析。分析结果表明,除了非线性平方敏感误差对不同角速率值的影响近似相同外,其他各项误差随着工作角速率的大小变化而变化,误差对小角速率工作测量影响较大。因此,使用微机械陀螺仪对精密仪器运动角速率测量时,要对其测量结果按标定曲线进行修正。该研究作为实际测量速率的有效补偿,提高了测量精度,具有一定的实际应用价值。

太赫兹目标RCS测量误差估计方法及其应用

太赫兹频段下非标准体目标的雷达散射截面积(RCS)较难通过电磁散射计算的方式得到结果,实验测量得到目标RCS成为该频段下的可行方案。然而,目前尚不具备系统性的估计指标来分析实测结果的误差特性。相比于目前较为简单的测量误差分析方式,本文提出3种太赫兹目标RCS测量误差估计指标;随后结合具有RCS解析解的目标,验证、分析所提估计指标的实用性和有效性。实测数据分析结果表明,本文提出的测量误差估计指标能够反映测量数据的误差规律与误差水平,具有实用性,有助于发现实验系统及实测数据处理中的有待优化之处。

A Dataset of Global Ocean Surface Currents for 1999-2007 Derived from Argo Float Trajectories: A Comparison with Surface Drifter and TAO Measurements

A dataset of surface current vectors with error estimate from 1999 to 2007 is derived from the trajectories of the Array for Real-time Geostrophic Oceanography (Argo) drifting on surface over the global ocean. The error of the estimated surface currents is about 4.7 cm s-1 which is equivalent to the accuracy of the currents determined from the surface drifters. Geographically, the Argo-derived surface currents can fill many gaps left by the Global Drifter Program due to the greater number of floats, and can provide a complementary in situ observational system for monitoring global ocean surface currents. The surface currents from the Argo floats are compared with the surface drifter-derived currents and the Tropical Atmosphere Ocean program (TAO) measurements. The comparisons show good agreement for both the current amplitude and the direction of surface currents. Results indicate the feasibility of obtaining ocean surface currents from the Argo array and of combining the surface currents from Argo and the ocean surface drifters for in situ mapping of the global surface currents. The authors also make the dataset available to users of interest for many types of applications.

Semiparametric Regression and Model Refining

This paper presents a semiparametric adjustment method suitable for general cases.Assuming that the regularizer matrix is positive definite,the calculation method is discussed and the corresponding formulae are presented.Finally,a simulated adjustment problem is constructed to explain the method given in this paper.The results from the semiparametric model and G_M model are compared.The results demonstrate that the model errors or the systematic errors of the observations can be detected correctly with the semiparametric estimate method.

Influence of age in estimating maximal oxygen uptake

Objective To assess the influence of age on the error of estimate （EE） of maximal oxygen uptake （VO2max） using sex and population specific-equations in cycle ergometer exercise testing, since estimated VO2 max is associated with a substantial EE, often exceeding 20%, possibly due to intrinsic variability of mechanical efficiency. Methods 1850 adults （68% men）, aged 18 to 91 years, underwent maximal cycle ergometer cardiopulmonary exercise testing. Cardiorespiratory fitness （CRF） was assessed relative to sex and age [younger （18 to 35 years）, middle-aged （36 to 60 years） and older （〉 60 years）]. VO2max [mL.（kg.min）-1] was directly measured by assessment of gas exchange and estimated using sex and population specific-equations. Measured and estimated values of VO2max and related EE were compared among the three age- and sex-specific groups. Results Directly measured VO2max of men and women were 29.5 ± 10.5 mL.（kg.min）-1 and 24.2 ± 9.0 mL.（kg·min） -1 （P 〈 0.01）. EE [mL·（kg·min）-1] and percent errors （%E） for men and women had similar values, 0.5 ± 3.2 and 0.4 ± 2.9 mL·（kg·min）-1, and -0.8 ± 13.1% and -1.7 ± 15.4% （P 〉 0.05）, respectively. EE and %E for each age-group were, respectively, for men： younger = 1.9 ± 4.1 mL·（kg·min）-1 and 3.8 ± 10.5%, middle-aged = 0.6 ± 3.1 mL.（kg·min）-1 and 0.4 ± 10.3%, older = -0.2 ± 2.7 mL·（kg·min） -1 and -4.2 ± 16.6% （P 〈 0.01）; and for women： younger = 1.2 ± 3.1 mL.（kg.min）-1 and 2.7 ±10.0%, middle-aged = 0.7 ± 2.8 mL·（kg·min）-1 and 0.5 ± 11.1%, older = -0.8 ± 2.3 mL-（kg·min）-1 and -9.5 ± 22.4% （P 〈 0.01）. Conclusion VO2max were underestimated in younger age-groups and were overestimated in older age groups. Age significantly influences the magnitude of the EE of VO2max in both men and women and should be considered when CRF is estimated using population specific equations, rather than directly measured.

Real time remaining useful life prediction based on nonlinear Wiener based degradation processes with measurement errors

Real time remaining useful life(RUL) prediction based on condition monitoring is an essential part in condition based maintenance(CBM). In the current methods about the real time RUL prediction of the nonlinear degradation process, the measurement error is not considered and forecasting uncertainty is large. Therefore, an approximate analytical RUL distribution in a closed-form of a nonlinear Wiener based degradation process with measurement errors was proposed. The maximum likelihood estimation approach was used to estimate the unknown fixed parameters in the proposed model. When the newly observed data are available, the random parameter is updated by the Bayesian method to make the estimation adapt to the item's individual characteristic and reduce the uncertainty of the estimation. The simulation results show that considering measurement errors in the degradation process can significantly improve the accuracy of real time RUL prediction.

Corrected empirical likelihood for a class of generalized linear measurement error models

Generalized linear measurement error models, such as Gaussian regression, Poisson regression and logistic regression, are considered. To eliminate the effects of measurement error on parameter estimation, a corrected empirical likelihood method is proposed to make statistical inference for a class of generalized linear measurement error models based on the moment identities of the corrected score function. The asymptotic distribution of the empirical log-likelihood ratio for the regression parameter is proved to be a Chi-squared distribution under some regularity conditions. The corresponding maximum empirical likelihood estimator of the regression parameter π is derived, and the asymptotic normality is shown. Furthermore, we consider the construction of the confidence intervals for one component of the regression parameter by using the partial profile empirical likelihood. Simulation studies are conducted to assess the finite sample performance. A real data set from the ACTG 175 study is used for illustrating the proposed method.

Asymptotic Normality of LS Estimate in Simple Linear EV Regression Model

Though EV model is theoretically more appropriate for applications in which measurement errors exist, people are still more inclined to use the ordinary regression models and the traditional LS method owing to the difficulties of statistical inference and computation. So it is meaningful to study the performance of LS estimate in EV model. In this article we obtain general conditions guaranteeing the asymptotic normality of the estimates of regression coefficients in the linear EV model. It is noticeable that the result is in some way different from the corresponding result in the ordinary regression model.