宽频带圆极化缝隙螺旋天线的设计

研究了一种宽阻抗带宽和宽圆极化轴比带宽的缝隙螺旋天线。天线印制在由FR4 介质基板构建的 方形柱状结构的内外表面,两组长短不同的缝隙螺旋臂印制在介质基板外表面并延伸至天线顶部;一条弯折的微带 线作为馈电网络印制在介质基板内表面,通过对各缝隙耦合馈电,实现天线宽阻抗带宽和轴比带宽。实测结果表 明:天线尺寸为0. 111λ0 ×0. 111λ0 ×0. 221λ0(λ0 为北斗B2 中心频率1. 207 GHz 对应的自由空间波长),S11 ≤ -10 dB 的阻抗带宽为1. 158~1. 778 GHz,轴比≤3 dB 的圆极化带宽为1. 133~1. 918 GHz。该天线采用缝隙螺旋结构,通过 简易的馈电网络实现天线小型化和宽频带特性,在卫星导航系统中具有较好的应用前景。     

Formal Specification and Quantitative Analysis of a Constellation of Navigation Satellites

Navigation satellites are a core component of navigation satellite‐based systems such as Global Positioning System, Global Navigation Satellite System and Galileo, which provide location and timing information for a variety of uses. Such satellites are designed for operating on orbit to perform tasks and have lifetimes of 10 years or more. Reliability, availability and maintainability analysis of systems has been indispensable in the design phase of satellites in order to achieve minimum failures or to increase mean time between failures and thus to plan maintenance strategies, optimise reliability and maximise availability. In this paper, we present formal models of both a single satellite and a navigation satellite constellation and logical specification of their reliability, availability and maintainability properties, respectively. The probabilistic model checker PRISM has been used to perform automated analysis of these quantitative properties. Copyright © 2014 John Wiley & Sons, Ltd.     

基于Kinect传感器的移动机器人环境检测及行为学习

研究了一种基于深度图像和强化学习算法的移动机器人导航行为学习方法。该方法利用机器人装配的Kinect传感器检测工作环境信息,然后对获取的深度图像数据和视频图像进行处理、融合和识别,并由此构建机器人任务学习的状态空间,最终利用强化学习方法实现移动机器人的导航任务的自学习。该方法的有效性通过实验得到验证。实验表明,该方法能够使机器入具有较强的环境感知能力,并能够通过自学习的方式掌握行为能力。     

多无人水下航行器协同导航定位研究进展

介绍了多无人水下航行器(UUV)协同导航定位的原理,进而详细综述了国内外多UUV协作系统及多UUV协同导航定位系统的研究进展,重点研究和分析了水声测距及通信一体化、协同导航定位算法、协同导航定位观测、水下UUV组网等关键技术的研究特点和发展趋势。研究表明,随着海洋研究的不断深入,多UUV协同导航定位系统的发展将会更注重减小体积质量、适应复杂海洋环境和能源限制方面的研究。     

基于GPS与惯性组件的复合测姿系统设计

针对微小型载体空间有限而无法安装大型测姿系统,提出了一种低成本的微型复合测姿方案.复合测姿系统由单天线GPS和MEMS惯性组件构成.利用扩展卡尔曼滤波将单天线GPS和MEMS惯性组件信息融合,提高了姿态估计精度.室外车载实验结果表明,利用该复合测姿系统解算的滚角和俯仰角误差可控制在1°以内,航向角误差可控制在2°以内.     

Diode-Pumped Solid-State Lasers for Inertial Fusion Energy

We have begun building the Mercury laser system as the first in a series of new generation diode-pumped solid-state lasers for inertial fusion research. Mercury will integrate three key technologies: diodes, crystals, and gas cooling, within a unique laser architecture that is scalable to kilojoule and megajoule energy levels for fusion energy applications. The primary near-term performance goals include 10% electrical efficiencies at 10 Hz and 100J with a 2–10 ns pulse length at 1.047 m wavelength. When completed, Mercury will allow rep-rated target experiments with multiple chambers for high energy density physics research.     

功率方程在动力学求解中的一种应用方法

本文采用动力学普遍方程和功率方程相结合的方法求解质点系的动力学问题,从而使动力学普遍方程得到更广泛的应用,尤其是求解较复杂的动力学问题极为方便、有效．     

PAC Learning of One-Dimensional Patterns

Developing the ability to recognize a landmark from a visual image of a robot's current location is a fundamental problem in robotics. We consider the problem of PAC-learning the concept class of geometric patterns where the target geometric pattern is a configuration ofk points on the real line. Each instance is a configuration ofn points on the real line, where it is labeled according to whether or not it visually resembles the target pattern. To capture the notion of visual resemblance we use the Hausdorff metric. Informally, two geometric patternsP andQ resemble each other under the Hausdorff metric if every point on one pattern is close to some point on the other pattern. We relate the concept class of geometric patterns to the landmark matching problem and then present a polynomial-time algorithm that PAC-learns the class of one-dimensional geometric patterns. We also present some experimental results on how our algorithm performs.