EKF和UKF在惯导初始对准中的应用研究

针对初始对准的精度直接影响系统工作性能问题,在初始对准中引入扩展卡尔曼滤波算法（EKF）和Unscented卡尔曼滤波算法（UKF）。EKF算法将非线性系统线性化,是在非线性系统中常用的一种滤波方法 UKF算法没有把非线性系统近似为线性系统,而是使用确定性样本的方法处理非线性问题,使采样点的均值和方差完全符合实际的非线性系统的均值和方差。仿真结果显示,使用Unscented卡尔曼滤波时惯性导航系统初始对准的精度和稳定性都好于普遍使用的扩展卡尔曼滤波算法。     

基于自适应UKF的MEMS捷联惯导传递对准研究

在导航制导武器中,针对微机电捷联惯导系统（MEMS-SINS）非线性误差的状态估计精度差和模型扰动问题,通过分析无迹卡尔曼滤波（UKF）算法中初值的选取会直接影响观测值精度的问题,结合自适应估计原理,提出一种基于自适应因子的UKF算法,该算法能够自适应地调节系统模型的扰动和初值的偏差并根据新的协方差观测值更新方程。首先建立传递对准的大失准角误差模型,然后将该算法应用于该系统状态估计中,并与标准UKF进行比较,通过计算机仿真,传递对准速度提高3s左右,精度提高将近1倍。对两种算法结果进行对比分析表明,能够抑制传递对准系统初值选取的偏差影响,降低系统状态模型扰动的影响,提高传递对准的对准精度。     

鲁棒区间算法在能源规划中的应用

采用鲁棒区间算法解决目标函数和约束条件中的不确定性问题,开发一个鲁棒区间能源系统规划模型,通过求解得到模型全局最优解,以获得最小的能源成本及最优的能源分配方案．案例研究结果显示。通过此优化模型进行的综合环境约束的规划,能使城市能源消费整体结构得到优化,能源利用效率明显提高,可实现城市的能源经济环境的协调发展．     

鲁棒融合Kalman滤波在异步电机转速控制中的应用

协方差交叉融合算法是新兴的一种分布式融合算法,该算法避免了局部互协方差或相关阵的计算,算法简单,故得到了广泛的应用.以异步电机转速控制为应用背景,进行协方差交叉融合Kalman滤波算法的应用研究.相比已有的单传感器状态估计,所提出的协方差交叉融合状态估计算法估计精度更高.仿真实例分析说明了所提出的算法的有效性.     

非线性系统变结构鲁棒控制器的设计及其在电力系统中的应用

提出了一种非线性系统变结构鲁棒控制器设计方法，对切换平面的设计步骤和控制作用的求取作了详细论述，并给出了在电力系统中的应用实例及仿真结果．     

伪线性卡尔曼滤波在目标被动跟踪中的应用

在对目标进行纯方位跟踪时,伪线性卡尔曼滤波算法是一种有效的跟踪滤波方法,该方法可以很好地对目标运动状态进行估计。通过仿真证明了该方法降低了对模型精度的要求,具有较好的稳定性。     

无迹卡尔曼滤波在新型地形无源组合导航系统中的应用

为了提高自主水下航行器的导航精度,提出了一种新型地形无源组合导航系统.根据水下环境特点和航行器导航高精度和低成本的要求,采用捷联式惯性导航系统、地形辅助导航系统、多普勒速度声纳、电子磁罗经和利用UKF进行信息融合的导航计算机组成新型水下地形无源组合导航系统,并给出了EKF线性滤波方程、UKF非线性滤波方程和导航传感器量测方程.对比仿真实验表明,采用建议的传感器和UKF信息融合方式比采用EKF方式提高了水下航行器导航定位的精度.采用不同的导航传感器和UKF信息融合方法的地形无源组合导航系统可以有效地减小水下航行器导航位置误差,提高组合导航的稳定性和精度.     

线性矩阵不等式在鲁棒稳定性分析中的应用

1 MATLAB在鲁棒稳定性中的应用鲁棒控制是当今控制理论的一个研究热点,它是针对控制系统中的不确定性而提出来的.所谓控制系统的鲁棒性是指受控系统在存在内部不确定性和外部干扰的情况下,设计静态或动态的反馈控制器,使闭环系统满足预定的某项或某几项性能指标;是衡量系统中存     

滤波算法在测井数据预处理中的应用

采集到的测井数据因受外界的干扰和仪器本身特性的影响,往往呈现出非线性、非平稳性和非光滑性等特点,给后续的测井数据的分析带来了误差甚至是错误。介绍了对测井数据进行预处理的3种平滑方法,并着重介绍了lowss方法在MATLAB操作平台上进行算法编程实现。最后,对这3种方法进行了比较。     

基于TDOA/Doppler测量的联邦UKF移动位置估计算法(英文)

为了进一步提高移动台的跟踪和定位性能,提出了一种基于联邦滤波结构和简化UKF的移动位置最优估计与融合新方法.该算法以Singer移动台运动模型作为参考系统,以简化UKF滤波器作为子滤波器,对2组独立检测的TDOA和Doppler测量值进行局部估计;然后在主滤波器中,对子滤波器的估计结果按标量加权进行最优融合,得到全局最优或次最优融合估计结果;最后主滤波器利用全局估计结果对子滤波器和参考系统进行反馈和信息重置,以进行下一步估计.仿真试验中,对该算法用于移动台位置估计的效果和性能进行评估,并与基于TDOA和基于Doppler的简化UKF方法做比较.仿真结果表明,该算法能有效降低移动台位置估计的误差和方差,具有良好的均方根误差和均值误差CDF性能.     

基于图像处理和UKF算法的小球位置预测

针对球的非线性运动和系统延时等因素对球的位置预测精度的影响,采用帧差法和改进的霍夫圆检测方法得到球的位置信息,并应用无迹卡尔曼滤波(UKF)算法对球的运动轨迹进行预测。通过摄像机采集球在自由滚动和发生碰撞时的几组图像,在上位机VC6.0软件上实现对球位置信息采集和处理,得到球准确的预测位置信息,满足决策系统的对球位置信息的要求,从而验证了算法的有效性。     

Gaussian particle filter based pose and motion estimation

Determination of relative three-dimensional (3D) position, orientation, and relative motion between two reference frames is an important problem in robotic guidance, manipulation, and assembly as well as in other fields such as photogrammetry. A solution to pose and motion estimation problem that uses two-dimensional (2D) intensity images from a single camera is de- sirable for real-time applications. The difficulty in performing this measurement is that the process of projecting 3D object features to 2D images is a nonlinear transformation. In this paper, the 3D transformation is modeled as a nonlinear stochastic system with the state estimation providing six degrees-of-freedom motion and position values, using line features in image plane as measuring inputs and dual quaternion to represent both rotation and translation in a unified notation. A filtering method called the Gaussian particle filter (GPF) based on the particle filtering concept is presented for 3D pose and motion estimation of a moving target from monocular image sequences. The method has been implemented with simulated data, and simulation results are provided along with comparisons to the extended Kalman filter (EKF) and the unscented Kalman filter (UKF) to show the relative advantages of the GPF. Simulation results showed that GPF is a superior alternative to EKF and UKF.     

抑制扩频系统中窄带干扰的新卡尔曼滤波算法

A new Kalman filtering algorithm based on estimation of spread spectrum signal before suppression of narrowband interference （NBI） in spread spectrum systems, using the dependence of autoregressive （AR） interference, is presented compared with performance of the ACM nonlinear filtering algorithm, simulation results show that the proposed algorithm has preferable performance, there is about 5 dB SNR improvement in average.     

机动目标跟踪的TIMM算法

针对如何避免或减少由于目标的机动运动所带来的估计误差问题,提出了具有门限的相互作用多模型估计(TIMM)的新算法.该算法主要应用于雷达目标自动跟踪系统中.TIMM算法在相互作用多模型估计器(IMM)算法的基础上引入门限控制器来提高跟踪精度,该算法同样适用于其他各种改进的IMM算法.通过2个不同的例子,对由TIMM和IMM这2种算法产生的均方根误差进行比较.仿真结果表明,同IMM算法相比较,TIMM算法可减少估计误差,从而提高机动目标的跟踪性能.     

Preparation for family-school partnerships within initial teacher education programmes in England

Abstract

The few studies conducted in Europe to date suggest that little attention is paid to pre-service teacher preparation for family-school partnerships (FSP) and that many teachers feel unprepared for such work. In England there has been little research in this area but a government review of best practice in parental involvement with schools concluded that ‘(t)eachers often lack the confidence and knowledge to work with parents …’. Given the apparent discrepancy between the need for teachers to be more knowledgeable about FSP and the lack of opportunity within initial teacher education (ITE) programmes to address the issues, we carried out a national survey of ITE providers in England in order to ascertain what provision is currently on offer. Our findings indicate that while there is overall recognition of the value of preparing trainee teachers to become confident and knowledgeable about home-school partnerships, ITE providers feel constrained by the lack of time available to them to explore this area in greater detail. The article concludes by discussing some of the challenges of both planning and delivering effective FSP provision within the ITE curriculum and how this might relate to future professional learning.     

SARS相关冠状病毒与其他已知冠状病毒的膜蛋白的多序列联配

1　Introduction　SARSisthefirstnewlyidentifiedseriousinfectiousdiseasethathumanbeingisfacingatthebeginningofthe 2 1stcentury .Ithasbeen primarilyrecognizedthatavariantofvirusfromthecoronavirusfamilymightbethecandidatepathogenofSARS ,asreportedbyWHO (WorldHealthOrganization)onApril 2 9,2 0 0 3(http ://www .who .int/csr/sarscountry/en) .　Coronaviruseswerefirstisolatedfromchickensin1937.Therearenowapproximately 15speciesinthisfamily.Coronavirusparticlesareirregularlyshaped ,roundabout 6 0 …     

Real-time localization estimator of mobile node in wireless sensor networks based on extended Kalman filter

Localization of the sensor nodes is a key supporting technology in wireless sensor networks (WSNs). In this paper, a real-time localization estimator of mobile node in WSNs based on extended Kalman filter (KF) is proposed. Mobile node movement model is analyzed and online sequential iterative method is used to compute location result. The detailed steps of mobile sensor node self-localization adopting extended Kalman filter (EKF) is designed. The simulation results show that the accuracy of the localization estimator scheme designed is better than those of maximum likelihood estimation (MLE) and traditional KF algorithm.     

Creating expansive learning opportunities in schools: the role of school leaders in initial teacher education partnerships

This article analyses the learning opportunities afforded pre-service teachers when participating in a primary school placement in London, England as part of their university teacher education course. Cultural historical activity theory is used as a theoretical framework to address how pre-service teacher learning opportunities are constructed. Building on a previous year-long ethnographic study which explored how and why pre-service teacher learning opportunities differed in school settings, this paper introduces a small scale pilot study. The study integrates developmental work research into an initial teacher education school/university partnership, and considers the role of the school leader in this. Possibilities for pre-service teachers, teachers and teacher educators to work together in a research process that is integral to an initial teacher education partnership are forwarded, with the aim of ensuring that critical enquiry and learning are kept at the forefront of the activity.     

Primary initial teacher trainees' perceptions of and perspectives on the role of the teaching assistant in English primary contexts

This article focuses on exploring initial teacher trainees' experiences and perspectives on the role of the teaching assistant (TA) in mainstream primary contexts. A backdrop of shrinking school budgets coupled with a ‘mainstream for all’ political agenda is contributing to growing uncertainty about the role of TAs in education. This article presents the results of a small-scale empirical study, involving 75 initial teacher trainees at the University of Cambridge. Trainees' perspectives regarding the roles/responsibilities that TAs have been seen to undertake and perceptions regarding the impact of the TAs they worked with were ascertained, with the aim of exploring how well current ITT content prepares students for an effective teacher/TA working relationship. Concept modelling was used as an analysis tool, to present visual representations of these perceptions. Trainees emphasised the administrative, pedagogical and pastoral roles that TAs were perceived to undertake and specifically highlighted the perceived ability of TAs to support students displaying needs relating to social, emotional and mental health. The findings highlight that the vague nature of current ITT content in relation to the role of TAs continues to serve as a barrier to students building coherent and consistent understandings of the successful deployment of TAs in English primary contexts.