基于多线程的惯导逻辑仿真器设计

针对惯导系统在载机静止状态下无法提供动态参数的问题,对惯导子系统进行数字仿真。在航电系统仿真中,采用1553 B总线与总线控制器和其他航电、非航电设备交联,通过以太网接收外部激励数据,采用多线程技术实现主备2个惯导并发运行,设计一种惯导逻辑仿真系统。阐述系统硬件结构和软件设计,建立惯导姿态仿真模型和位置仿真模型,实现惯导各种逻辑子过程。在某型飞机航电仿真系统中的联调证明,该仿真器能够准确接收外部激励源飞行信息、故障状态,经过结算后周期性地向总线控制器输出飞机位置数据、姿态数据等动态参数,执行某型飞机航电设计文档中相关惯导逻辑,并向总线控制器反馈惯导子系统状态。     

激光捷联惯导系统外场标校设备的设计与研制

为提高激光捷联惯导系统在外场的保障效率,提出了外场标校设备的总体设计方案、软件及硬件实现方法和标定算法,研制了外场标校设备.整个设备软硬件有机结合,具有自动化水平高、操作简便、体积小、重量轻、携带方便等优点,特别适用于外场维护.试验数据表明,第一导航小时CEP分别从0.91 nmile/h、1.05 nmile/h、0.78 nmile/h提高到 0.62 nmile/h、0.71 nmile/h、0.56 nmile/h,单台惯导系统标校时间小于90 min,大幅度提高了惯导系统的外场标校和保障效率,保障了惯导系统能正常可靠地服务于部队飞机.     

基于VS的捷联惯导系统仿真器设计

针对在实验室环境下实时获取飞机真实动态数据难度大的问题,借助飞行控制原理设计了飞机实际的飞行轨迹,并利用飞行轨迹产生的真实数据解算惯导误差及惯导参数,模拟了对惯导系统的动态导航.利用模块化设计思想,建立了捷联惯导系统的仿真轨迹模块、惯性器件参数输入模块、导航参数计算模块、视景仿真模块等,并在Visual Studio 2005开发环境下设计了捷联惯导系统仿真系统.用户界面直观简洁,通用性较强,可以实现人机交互、实时仿真等效果.仿真结果与惯导系统误差特征一致,验证了仿真器所用捷联惯导系统算法的正确性.     

高精度IMU标校三轴转台关键参数的测试方法

为了保证三轴转台的关键参数满足惯导系统标定、测试和验收要求,必须对关键参数进行检测和标校.目前三轴转台的关键参数主要包括:三个轴的垂直度、转台坐标系与地理坐标系误差角.这些关键参数验收及标校一直比较困难,尤其是三轴垂直度,目前国内只能在装配过程中检验,装配后由于轴里有滑环遮蔽光路所以无法检验.介绍了利用高精度IMU捷联惯组进行转台关键参数的标校的原理和方法.最后通过在转台上的实际测试验证了方法的可行性.     

基于数字孪生技术的惯导大数据分析与应用

从惯导大数据特征及应用问题出发,将数字孪生技术与惯导大数据分析、应用相结合,提出了基于数字孪生技术的惯导大数据分析与应用总体技术方案,详细介绍了惯导数字孪生五维模型及惯导数字孪生平台工具建设方案,给出了惯导多源异构模型集成方法,并对惯导大数据全生命周期赋能应用进行了系统总结。该方案为数字孪生、大数据赋能惯性技术的研究和应用提供一定的参考。     

一种新的船用捷联惯导系统数字仿真器的设计

以舰船的运动特性为依据,设计了一种新的船用捷联惯导系统数字仿真器;用VC++编程语言设计舰船运动轨迹;建立陀螺仪、加速度计的误差模型;用惯导系统姿态更新、位置更新、速度更新解算的结果与航迹点参数(真值)比较,得到惯导系统误差;应用表明,该仿真器能够灵活地模拟出舰船在不同的运动状态下船用捷联惯导系统的各种导航参数,为研究舰载条件下的捷联惯导系统传递对准技术提供了可靠的试验数据。     

基于旋转惯导双轴旋转系统的系统级标定

随着旋转调制惯导系统在空间飞行器上的逐步应用,低精度转台开始作为惯导系统的一部分参与导航过程,对基于旋转惯导系统双轴转台的光纤陀螺捷联惯导系统的系统级标定方法进行研究。建立附加约束条件和简化条件后的加速度计和陀螺的误差模型,在双轴转台上进行合理位置编排和转位,利用静态七位置下的捷联惯导输出数据做惯性导航,以速度误差和姿态误差作为观测量,建立Kalman滤波标定模型,系统辨识出三轴加速度计和陀螺的各项误差参数。通过计算机仿真验证,该方法能够准确利用滤波方法估计出陀螺和加表的共计21个器件误差参数,在工程上具有一定参考价值。     

掘进机全站仪与捷联惯导组合定位方法

针对基于全站仪的掘进机定位方法因井下粉尘过大等导致光路被遮挡而无法进行定位、基于捷联惯导的掘进机定位方法累计误差随时间推移逐渐增大的问题,提出一种掘进机全站仪与捷联惯导组合定位方法。首先,采用全站仪测量掘进机位置参数,采用捷联惯导测量掘进机位姿参数并进行解算;然后,将捷联惯导测量的掘进机所在位置经纬度转换为西安80坐标系下的坐标值,实现与全站仪测量坐标系的统一;最后,采用卡尔曼滤波方法将全站仪与捷联惯导测量数据进行融合,获取掘进机位姿数据。试验结果表明该方法具有较高的定位精度:x方向的定位误差最大值为0.029 1m,最小值为0.010 0m,平均值为0.019 93m;y方向的定位误差最大值为0.029 5m,最小值为0.011 0m,平均值为0.018 26m。     

游移方位捷联惯导系统软件测试与仿真

用C语言实现了游移方位捷联惯导系统的实时软件仿真;分别以圆球和参考旋转椭球体作为地球模型进行导航参数计算;用圆球模型下的飞行轨迹数据对圆球模型,椭球模型,加惯性元件误差的椭球模型下的捷联惯导系统导航参数进行测试;提出将速度通道和高度通道联立求解的方法.以提高速度,高度计算的准确性;并解决了导航参数解算中出现的计算周期同步问题;分析了误差来源,比较了圆球和参考旋转椭球体之间的差异;验证了该惯导系统仿真的正确性,证明了该测试方法的可行性。     

一种新的导航系统仿真轨迹设计方法

飞行轨迹动态参数是验证捷联惯导系统、组合导航系统等算法有效性的重要依据。利用飞行控制原理设计了一种通用的飞机飞行仿真轨迹,并在Visual Studio 2005开发环境下设计了飞行轨迹仿真软件。该仿真软件产生的数据有效地测试了某型导航系统导航参数的误差精度,验证了捷联惯导算法的正确性。     

Mining churning behaviors and developing retention strategies based on a partial least squares (PLS) model

In a very competitive mobile telecommunication business environment, marketing managers need a business intelligence model that allows them to maintain an optimal (at least a near optimal) level of churners very effectively and efficiently while minimizing the costs throughout their marketing programs. As a first step toward optimal churn management program for marketing managers, this paper focuses on building an accurate and concise predictive model for the purpose of churn prediction utilizing a partial least squares (PLS)-based methodology on highly correlated data sets among variables. A preliminary experiment demonstrates that the presented model provides more accurate performance than traditional prediction models and identifies key variables to better understand churning behaviors. Further, a set of simple churn marketing programs—device management, overage management, and complaint management strategies—is presented and discussed.     

Exploring convenience in mobile commerce: Moderating effects of gender

To date, little research has examined gender difference in how convenience is perceived in mobile commerce (m-commerce). The current work presents and tests a theoretical model partially based on Technology Acceptance Model (TAM), and posits a sequential relationship among four primary dimensions: (1) intrinsic attributes of mobile device—portability and interface design; (2) ease of use; (3) extrinsic attributes of mobile device—simultaneity, speed, and searchability; and (4) perceived convenience of m-commerce. We posit that physical attributes of mobile device (portability and interface design) are antecedents of ease of use, which in turn determines three extrinsic attributes (simultaneity, speed, and searchability). The final dependent variable is perceived convenience. Based on prior research on TAM and gender theories, the study proposes 16 hypotheses, of which our data support 12. Our results indicate that the link between interface design and ease of use holds a key to motivate females’ use of m-commerce. In closing, implications are discussed while important limitations are recognized along with future research suggestions.     

Study on design and application of fully automatic miniature surface plasmon resonance concentration analyzer

A fully automatic miniature surface plasmon resonance (SPR) concentration analyzer having high performance and low cost and developed using a Spreeta™ sensor was designed for field applications and concentration analysis. As in the case of Biacore™ instruments, the automatic sampling system of this device can introduce air segments between the sample/regeneration solution and buffer solution in the pipeline, which effectively prevents mixing of the solutions. A temperature sensor (AD 590) and temperature compensation method are used, which make the device insensitive to temperature fluctuations. A real-time data-smoothing algorithm for the SPR detection data is adopted; this can reduce the noise level to 5 × 10⁻⁷ RIU (refractive index units). The noise level of the sensorgram is 3.5% of the original level. Two types of self-prepared sensing chips—SMX-BSA (bovine serum albumin coated with sulfamethoxazole) and SMX-CM5 (carboxymethyl dextran coated with sulfamethoxazole)—are used to analyze the concentrations of sulfamethoxazole (SMX) standard solutions. Each chip's SMX calibration curve is established within the measurement range of 0-2000 ng/ml, and both limits of detection (LOD) are 2 ng/ml. One cycle of assay time is less than 15 min.     

DALASS: Variable selection in discriminant analysis via the LASSO

The objective of DALASS is to simplify the interpretation of Fisher's discriminant function coefficients. The DALASS problem—discriminant analysis (DA) modified so that the canonical variates satisfy the LASSO constraint—is formulated as a dynamical system on the unit sphere. Both standard and orthogonal canonical variates are considered. The globally convergent continuous-time algorithms are illustrated numerically and applied to some well-known data sets.     

Improving the usability of standard schemas

Due to the development of XML and other data models such as OWL and RDF, sharing data is an increasingly common task since these data models allow simple syntactic translation of data between applications. However, in order for data to be shared semantically, there must be a way to ensure that concepts are the same. One approach is to employ commonly usedschemas—called standard schemas —which help guarantee that syntactically identical objects have semantically similar meanings. As a result of the spread of data sharing, there has been widespread adoption of standard schemas in a broad range of disciplines and for a wide variety of applications within a very short period of time. However, standard schemas are still in their infancy and have not yet matured or been thoroughly evaluated. It is imperative that the data management research community takes a closer look at how well these standard schemas have fared in real-world applications to identify not only their advantages, but also the operational challenges that real users face.     

On the data consumption benefits of accepting increased uncertainty

In the context of learning paradigms of identification in the limit, we address the question: why is uncertainty sometimes desirable? We use mind change bounds on the output hypotheses as a measure of uncertainty and interpret ‘desirable’ as reduction in data memorization, also defined in terms of mind change bounds. The resulting model is closely related to iterative learning with bounded mind change complexity, but the dual use of mind change bounds — for hypotheses and for data — is a key distinctive feature of our approach. We show that situations exist where the more mind changes the learner is willing to accept, the less the amount of data it needs to remember in order to converge to the correct hypothesis. We also investigate relationships between our model and learning from good examples, set-driven, monotonic and strong-monotonic learners, as well as class-comprising versus class-preserving learnability.     

Plugging the holes in host-based authentication

Many of the most popular computer and network authentication schemes commonly in use today are surprisingly weak. Some progress has been made in recent years, though stronger schemes have yet to be widely adopted. The problems are partly technical — a variety of mechanisms have been invented; partly political — the not invented here syndrome; and partly Political — government attitudes towards cryptographic technology.In this paper, the vulnerabilities in commonly used authentication schemes are discussed. An overview of the emerging technologies and some of the problems they solve — and cause! — is also presented.     

An evolutionary algorithm for robust regression

A drawback of robust statistical techniques is the increased computational effort often needed as compared to non-robust methods. Particularly, robust estimators possessing the exact fit property are NP-hard to compute. This means that—under the widely believed assumption that the computational complexity classes NP and P are not equal—there is no hope to compute exact solutions for large high dimensional data sets. To tackle this problem, search heuristics are used to compute NP-hard estimators in high dimensions. A new evolutionary algorithm that is applicable to different robust estimators is presented. Further, variants of this evolutionary algorithm for selected estimators—most prominently least trimmed squares and least median of squares—are introduced and shown to outperform existing popular search heuristics in difficult data situations. The results increase the applicability of robust methods and underline the usefulness of evolutionary algorithms for computational statistics.     

An efficient implementation of the Min-Min heuristic

Min—Min is a popular heuristic for scheduling tasks to heterogeneous computational resources, which has been applied either directly or as part of more sophisticated heuristics. However, for large scenarios such as grid computing platforms, the time complexity of a straightforward implementation of Min—Min, which is quadratic in the number of tasks, may be prohibitive. This has motivated the development of high performance computing (HPC) implementations, and the use of simpler heuristics for the sake of acceptable execution times. We propose a simple algorithm that implements Min—Min requiring only O(mn) operations for scheduling n tasks on m machines. Our experiments show, in practice, that a straightforward sequential implementation of this algorithm significantly outperforms other state of the art implementations of Min—Min, even compared to HPC implementations. In addition, the proposed algorithm is at least as suitable for parallelization as a direct implementation of Min—Min.     

Query optimization using restructured views: Theory and experiments

We study optimization of relational queries using materialized views, where views may be regular or restructured. In a restructured view, some data from the base table(s) are represented as metadata—that is, schema information, such as table and attribute names—or vice versa.