GIS技术在海缆路由设计中的应用

由于海底光（电）缆路由设计的复杂性、多维性和动态性以及传统平面设计方式不够形象直观的缺陷,使得应用GIS技术进行路由设计成为新的选择。文章介绍了GIS技术的发展现状、关键技术,归纳了海缆路由设计的流程、对象,重点对GIS技术在海缆路由设计中的应用进行探讨,并指出基于3D GIS技术的海缆可视化路由设计是发展趋势。     

浅谈GIS在道路管理中存在的问题

充分利用GIS对空间信息的管理能力和生动形象的图形表现形式,结合交通系统的具体特点,开发适合现代变通发展需要GIS,具有鲜明的实际意义。     

GPS卫星导航定位系统初探

主要介绍了GPS卫星导航定位系统的组成、工作原理、特点及其在民用领域的应用。     

基于卡尔曼滤波的GPS/DR导航信息融合方法

为了有效地实现GPS/DR(Global Positioning System/Dead Reckoning)组合导航系统的信息融合,提高GPS/DR组合导航系统的精度和可靠性,分析了传统的利用全球定位系统(GPS)与航位推算系统(DR)跟踪车辆位置方法的特点,结合GPS和航位推算DR两种定位方式的优点,在车辆定位技术中采用GPS/DR组合定位技术,构建了基于卡尔曼滤波技术的自适应联合卡尔曼滤波器,使用Matlab软件工具进行了计算机仿真验证,从软件集成的角度探讨了GPS/DR组合定位技术的串口通信等关键技术的软件实现问题,给出了GPS单独导航、DR单独导航和GPS/DR组合导航三种工作状态下的位置误差。从对比中可以看出,组合系统能在任何情况下实现车辆的实时、可靠、准确的定位,定位误差最小,同时还可以减小甚至消除推算定位系统随时间积累的误差。     

基于AIS的舰载雷达标校方法研究

雷达标校是战场精确打击和组网雷达数据融合的前提,为提高舰载雷达数据融合的有效性和目标探测精度,文中提出了基于AIS接收标校目标定位信息的舰载雷达系统标校方法,分析了标校的基本原理和主要误差源,详细给出了目标真值的大地测量主题解算方法,最后得出标校理论精度范围,并通过仿真分析得以验证.该标校方法过程简单,操作方便,真值精度高,通用性强,同时适用于静态标校和动态标校.     

利用船载GPS姿态仪提高磁场的测量精度

舰船的磁场是舰船物理场的重要信息,对它的测量对研究舰船物理场的特征具有重要的意义。然而,在海水中舰船的磁场信息势必受到舰船姿态信息变化的影响,因此提出修正舰船姿态信息对磁场测量影响的方法。本文具体论述了用船载GPS姿态仪获取舰船姿态信息的原理和实现方法,并提出了用舰船姿态信息修正舰船磁场的计算方法,从而提高舰船磁场的测量精度。     

时间统一系统同步误差测量方法研究

传统的人工时间同步误差的测量方法存在操作复杂和效率低下的缺点。为解决这些问题,提出一种同步误差的测量方法,该方法基于复杂可编程逻辑器件（CPLD）技术,并利用全球定位系统来测量时间统一系统的同步误差。相对于传统的测量方法,该方法显著提高了同步误差测量的智能化程度,减轻了测试人员的工作量。通过实验,验证了本设计方案的可行性及正确性。     

A traffic analysis zone definition: a new methodology and algorithm

This paper develops a comprehensive approach to the definition of transportation analysis zones (TAZ), and therein, presents a new methodology and algorithm for the definition of TAZ embedded in geographic information systems software, improves the base algorithm with several local algorithms, and comprehensively analyses the obtained results. The results obtained are then compared to these presently used in the transportation analysis process of the Lisbon Metropolitan Area. The proposed algorithm presents a new methodology for TAZ design based on a smoothed density surface of geocoded travel demand data. The algorithm aims to minimise the loss of information when moving from a continuous representation of the origin and destination of each trip to their discrete representations through zones, and focuses on the trade-off between the statistical precision, geographical error, and the percentage of intra-zonal trips of the resulting OD matrix. The results for the Lisbon Metropolitan Area case study suggest a significant improvement in OD matrix estimates compared to current transportation analysis practises based on administrative units.

Passenger travel characteristics and bus operational states: a study based on IC card and GPS data in Yinchuan,China

ABSTRACT

In recent years, public transport has been developing rapidly and producing large amounts of traffic data. Emerging big data-mining techniques enable the application of these data in a variety of ways. This study uses bus intelligent card (IC card) data and global positioning system (GPS) data to estimate passenger boarding and alighting stations. First, an estimation model for boarding stations is introduced to determine passenger boarding stations. Then, the authors propose an innovative uplink and downlink information identification model (UDI) to generate information for estimating alighting stations. Subsequently, the estimation model for the alighting stations is introduced. In addition, a transfer station identification model is also developed to determine transfer stations. These models are applied to Yinchuan, China to analyze passenger flow characteristics and bus operations. The authors obtain passenger flows based on stations (stops), bus lines, and traffic analysis zones (TAZ) during weekdays and weekends. Moreover, average bus operational speeds are obtained. These findings can be used in bus network planning and optimization as well as bus operation scheduling.     

Co-location decision tree for enhancing decision-making of pavement maintenance and rehabilitation

This paper presents a new decision tree induction method, called co-location-based decision tree (CL-DT), to enhance the decision-making of pavement maintenance and rehabilitation strategies. The proposed algorithm utilizes the co-location characteristics of spatial attribute data in the pavement database. The paper first presented the co-location mining algorithm, including spatial attribute data selection, determination of rough candidate co-locations, determination of candidate co-locations, pruning the non-prevalent co-locations, and induction of co-location rules, and then focused on the development of the co-location decision tree (CL-DT) algorithm, which includes the non-spatial attribute data selection, co-location algorithm modeling, node merging criteria, and co-location decision tree induction. A pavement database covering four counties, which are provided by North Carolina Department of Transportation (NCDOT), is used to verify the proposed method. The experimental results demonstrated that (1) the proposed CL-DT algorithm can make a better decision, and has higher accuracy than the existing decision tree methods do; (2) the training data can be fully played roles in contribution to decision tree induction and the computational time taken for the tree growing, tree drawing and rule generation is largely decreased; (3) quantity and locations of six treatment strategies proposed by the ITRC and by CL-DT is much close for each treatment strategy.