A Fast Global Node Selection Algorithm for Bearings-only Target Localization

In the target tracking, the nodes aggregate their observations of the directions of arrival of the target. The network then uses an extended Kalman filter （EKF） to combine the measurements from multiple snapshots to track the target. In order to rapidly select the best subset of nodes to localize the target with the minimum mean square position error and low power consumption, this paper proposes a simple algorithm, which uses the location information of the target and the network. The lower botmd of localization error is utilized according to the distances between the target and the selected active nodes. Furthermore, the direction likelihoods of the active nodes is predicted by way of the node/target bearing distributing relationships.     

WL10型近红外反射式光电传感器的研制

依据光学电子学的相关原理,针对烟草行业自动生产过程中对传感器的需要,研制了ＷＬ１０型近红外反射光电传感器,并成功地应用于烟草行业的生产线上。     

低成本无人机传感器配置方案的设计与仿真

以降低无人机制造成本为目标,在保证无人机安全自主飞行的前提下,提出了基于GPS和垂直陀螺、GPS和三轴速率陀螺及GPS和低成本惯性组件的3种低成本传感器配置方案,并针对每种方案在工程中遇到的问题,采用低通滤波、高通滤波和卡尔曼滤波等数据融合算法予以解决,最后在MATLAB平台下对每种传感器配置方案进行仿真验证.研究对比表明,对于自身稳定性较好的无人机,该3种传感器配置方案均能够实现姿态控制、高度控制、滚转控制以及航迹控制.     

基于红外传感器智能车的设计与实现

目的结合飞思卡尔全国智能车大赛,介绍一种基于红外反射式光电传感器路径识别的智能车控制系统;方法利用10路红外光电传感器构成光电传感器阵列采集路面信息,采用霍尔式速度传感器采集小车速度信息;结果单片机获得路径信息和车速信息后,用以控制智能车的舵机转向,同时对电机进行调速,实现智能车沿着既定的跑道自主运行;结论试验证明,系统能够较好地满足智能车对路径识别和稳定性的要求,具备一定的抗干扰能力,能够快速平稳地自动寻迹行驶。     

基于不确定传感器状态的机载系统多层故障诊断方法

准确的机载系统故障诊断是保证飞机安全飞行和实现经济效益最大化的重要途径。然而传感器受到内外部环境条件的影响而不可避免的存在检测状态的不确定性,因此基于单个传感器或局部区域传感器综合检测结果的方法难以完全保证故障诊断的有效性和正确性。针对飞机机载系统的结构和工作原理,充分利用系统中不同层级、不同区域传感器检测特征之间的关联关系,考虑单个传感器本身存在的不确定性,构建了传感器信息前向融合与反向校验相结合的分层诊断决策方法,实现了对系统状态和传感器状态的双重估计与更新,克服了单一传感器故障对系统诊断推理准确度的影响。该方法较传统故障诊断模型,不再依赖某一个或某一类传感器信息的绝对可靠,在实现系统级的准确故障诊断同时,还能判断具体某一传感器本身是否发生虚拟警。在飞机液压系统故障诊断案例中,新方法成功将系统故障诊断的虚警率降低了96%,传感器的不确定度降低了84%。     

Fast Online Approximation for Hard Support Vector Regression and Its Application to Analytical Redundancy for Aeroengines

The hard support vector regression attracts little attention owing to the overfitting phenomenon. Recently, a fast offline method has been proposed to approximately train the hard support vector regression with the generation performance comparable to the soft support vector regression. Based on this achievement, this article advances a fast online approximation called the hard support vector regression (FOAHSVR for short). By adopting the greedy stagewise and iterative strategies, it is capable of online estimating parameters of complicated systems. In order to verify the effectiveness of the FOAHSVR, an FOAHSVR-based analytical redundancy for aeroengines is developed. Experiments on the sensor failure and drift evidence the viability and feasibility of the analytical redundancy for aeroengines together with its base-FOAHSVR. In addition, the FOAHSVR is anticipated to find applications in other scientific-technical fields.     

The Cassini Cosmic Dust Analyzer

The Cassini-Huygens Cosmic Dust Analyzer (CDA) is intended to provide direct observations of dust grains with masses between 10⁻¹⁹ and 10⁻⁹ kg in interplanetary space and in the jovian and saturnian systems, to investigate their physical, chemical and dynamical properties as functions of the distances to the Sun, to Jupiter and to Saturn and its satellites and rings, to study their interaction with the saturnian rings, satellites and magnetosphere. Chemical composition of interplanetary meteoroids will be compared with asteroidal and cometary dust, as well as with Saturn dust, ejecta from rings and satellites. Ring and satellites phenomena which might be effects of meteoroid impacts will be compared with the interplanetary dust environment. Electrical charges of particulate matter in the magnetosphere and its consequences will be studied, e.g. the effects of the ambient plasma and the magnetic field on the trajectories of dust particles as well as fragmentation of particles due to electrostatic disruption.The investigation will be performed with an instrument that measures the mass, composition, electric charge, speed, and flight direction of individual dust particles. It is a highly reliable and versatile instrument with a mass sensitivity 10⁶ times higher than that of the Pioneer 10 and 11 dust detectors which measured dust in the saturnian system. The Cosmic Dust Analyzer has significant inheritance from former space instrumentation developed for the VEGA, Giotto, Galileo, and Ulysses missions. It will reliably measure impacts from as low as 1 impact per month up to 10⁴ impacts per second. The instrument weighs 17 kg and consumes 12 W, the integrated time-of-flight mass spectrometer has a mass resolution of up to 50. The nominal data transmission rate is 524 bits/s and varies between 50 and 4192 bps.This revised version was published online in July 2005 with a corrected cover date.     

一种改进的星图降噪算法研究

在星敏感器的使用过程中,由于外界环境的影响及传感器自身的限制,拍摄出来的星图不可避免地存在一些噪声,因此对星图进行去噪处理是一项非常重要的工作。针对传统高斯模板滤波存在的引入邻域噪声、无法自行根据星图特性修正等造成去噪效果不好的问题,提出了一种改进的星图降噪算法。该方法在滤波前先进行坏点剔除工作,并采用高斯低通滤波与高通滤波结合的方式对图像进行处理,在抑制噪声的同时有效地保留了星点信号。通过阐述星敏感器的工作原理,分析星图的噪声特性,对星图滤波去噪算法进行研究,并进行模拟星图影像提取星点坐标实验。结果表明：使用该算法进行滤波比传统的高斯滤波算法提取的质心坐标精确度更高,较传统方法横坐标提高0.00538个像素点,纵坐标提高0.0077个像素点,证实了图像处理算法的有效性。     

基于ANSYS的同面多电极电容传感器仿真研究

同面多电极电容传感器是一种新的飞机复合材料构件损伤检测技术,该检测技术的正问题中敏感场分布函数的计算要涉及到静电场中电容计算问题。在仿真研究中,电容要通过场的数值计算方法来求得。本文介绍了如何使用ANSYS有限元分析计算同面多电极电容传感器中的各电极对之间的电容,对检测材料发生异常及传感器参数改变时电容的变化进行了分析,为损伤检测的特征提取和逆问题图像重构提供了仿真数据。     

角位移传感器校准方法及不确定度分析

描述了角位移传感器的迟滞、重复性、非线性等主要技术指标的校准方法、校准步骤和数据处理方法、测量不确定度评定方法。