System identification for nonlinear maneuvering of large tankers using artificial neural network

This paper deals with the application of nonparametric system identification to a nonlinear maneuvering model for large tankers using artificial neural network method. The three coupled maneuvering equations in this model for large tankers contain linear and nonlinear terms and instead of attempting to determine the parameters (i.e. hydrodynamic derivatives) associated with nonlinear terms, all nonlinear terms are clubbed together to form one unknown time function per equation which are sought to be represented by the neural network coefficients. The time series used in training the network are obtained from simulated data of zigzag maneuvers and the proposed method has been applied to these data. The neural network scheme adopted in this work has one middle or hidden layer of neurons and it employs the Levenberg–Marquardt algorithm. Using the best choices for the number of hidden layer neurons, length of training data, convergence tolerance etc., the performance of the proposed neural network model has been investigated and conclusions drawn.     

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机载三维成像系统

本文简要地阐述了新型机载三维成像系统的产生环境、原理、技术结构、特色及应用领域 ,介绍了飞行检测、应用飞行所取得的成果。为实现高效遥感对地观测体系迈出的第一步。     

德国迁都柏林过程中的地球信息技术─-祝贺陈述彭院士2000年2月14日八十华诞生日快乐

联邦德国议会1991年决定, 议会与政府核心部门在2000年前从波恩迁回柏林 ,波恩保留联邦行政管理中心的功能。为了按时准确地规划和完成落实迁都建设工程,在柏林建设国家行政办公设施和国家工作人员生活居住设施,解决波恩地区因国家机关迁离而遭受的损失,参加建设的许多部门应用了地球信息技术。文中介绍了“柏林房地产信息系统”,“联邦议会与政府核心区建设信息系统”,“物业管理信息系统”,“波恩地区经济地理信息系统”以及地球信息技术在交通和环境管理中的应用。     

华北区域分米级北斗地基增强服务系统构建及精度分析

利用国家级北斗连续运行基准站和省级区域北斗CORS站,基于国家卫星导航定位服务平台,通过改造和直接利用的方式,在华北平原构建了我国首个跨区域北斗分米级地基增强服务系统。经采用双频终端实地测试,该系统覆盖京津冀晋全部区域及内蒙古部分区域,采用GPS+北斗双模定位静态精度达到分米级,动态定位精度达到亚米级,单北斗模式定位精度略低,但仍在分米-亚米量级,极大地提高了我国北斗导航系统的高精度应用能力,拓宽了我国北斗民用导航的应用范围和领域,可满足高精度北斗实时导航、定位服务的应用需求。     

Developing a comprehensive evaluation method for Interconnected River System Network assessment: A case study in Tangxun Lake group

Journal of Geographical Sciences - The Interconnected River System Network (IRSN) plays a crucial role in water resource allocation, water ecological restoration and water quality improvement. It...     

GIS支持下的土地资源环境承载力评价——以荣成市为例

随着人类生产活动的日益加剧,土地资源环境已逐渐成为制约社会经济发展的主要因素。基于荣成市土地资源环境要素,利用层次分析法构建了区域土地资源环境承载力评价体系。对土地资源进行基础性评价,在GIS技术支持下计算各项指标分值,并得出承载状态压力指数;在基础性评价结果的基础上,对水资源、生态条件与环境质量进行修正性评价。结果显示,荣成市土地资源环境基础性评价为可载,基于水资源系统的综合承载状态为临界,基于生态条件与环境质量系统的综合承载状态为可载。     

Estimation of crowd density from UAVs images based on corner detection procedures and clustering analysis

With rapid developments in platforms and sensors technology in terms of digital cameras and video recordings, crowd monitoring has taken a considerable attentions in many disciplines such as psychology, sociology, engineering, and computer vision. This is due to the fact that, monitoring of the crowd is necessary to enhance safety and controllable movements to minimize the risk particularly in highly crowded incidents (e.g. sports). One of the platforms that have been extensively employed in crowd monitoring is unmanned aerial vehicles (UAVs), because UAVs have the capability to acquiring fast, low costs, high-resolution and real-time images over crowd areas. In addition, geo-referenced images can also be provided through integration of on-board positioning sensors (e.g. GPS/IMU) with vision sensors (digital cameras and laser scanner). In this paper, a new testing procedure based on feature from accelerated segment test (FAST) algorithms is introduced to detect the crowd features from UAV images taken from different camera orientations and positions. The proposed test started with converting a circle of 16 pixels surrounding the center pixel into a vector and sorting it in ascending/descending order. A single pixel which takes the ranking number 9 (for FAST-9) or 12 (for FAST-12) was then compared with the center pixel. Accuracy assessment in terms of completeness and correctness was used to assess the performance of the new testing procedure before and after filtering the crowd features. The results show that the proposed algorithms are able to extract crowd features from different UAV images. Overall, the values of Completeness range from 55 to 70 % whereas the range of correctness values was 91 to 94 %.     

SAGE测光巡天数据处理方法研究

元素丰度与星系演化(Stellar Abundance and Galactic Evolution,SAGE)是自主设计的能够准确计算恒星大气参数以及消光的新测光系统。对北天除银盘外共计约12 000 deg2的天区开展了SAGE系统测光巡天,计划获取约5亿颗恒星的高精度测光数据。单次曝光条件下100σ完备星等uSC～17. 3,vSAGE～16. 8(AB星等),这些为研究银河系提供宝贵的测光资料。介绍了巡天专用的数据处理程序的研究和开发,主要研究了针对单幅图像的快速自动化处理过程,重点介绍数据改正、天体测量校正、测光和流量定标过程,以及数据结果和数据质量检测等。     

基于GPS新型L5信号的地表雪深反演研究

利用GPS多路径反射信号测量地表雪深具有全天候和高时空分辨率的特点,因此其可作为一种代替气象站监测雪深的新手段。然而,先前大多数研究仅使用了GPS L1和L2C波段信噪比数据探测积雪深度。为验证新型的L5信号在雪深反演方面的优越性,本文阐述了GPS-R技术反演雪深的原理,利用Lomb-Scargle周期图法所处理的受积雪表层影响的信噪比数据计算了频谱振幅强度,通过获取频谱特征值与天线高度的关系求解雪深值,最后分别与L1反演结果和实测雪深数据进行了对比。试验结果表明：与现有的GPS-R测量雪深结果相比,利用新型的L5反射信号反演地表雪深的精度更佳;采用GPS-R技术探测雪深对把握测站区域内的雪深变化情况和淡水资源储量具有重要价值。