基于Delphi环境的GPS数据监测与采集

文章介绍了在Delphi环境下实现GPS数据监测采集的关键技术。GPS接收机通过串口与计算机进行通信,其数据格式为NMEA0183,程序利用MSComm控件实现数据接收,对数据进行处理后实时显示给用户,并将用户位置、时间、速度和航向等信息保存到数据库中,为监测开发GPS数据处理软件和其它导航系统定位信息输入提供依据和数据来源。     

基于多基线GPS舰船姿态测量系统研究

利用GPS对载体姿态进行测量是GPS应用的一个新领域。文章针对如何利用GPS载波相位信号实现舰船姿态测量进行了研究,并在此基础上进行了实验验证,测试结果表明该系统性能良好。     

基于天线选择的准正交空时码的自适应设计

为充分利用信道信息(Channel State Information,CSI)来改善准正交空时码(Quasi Orthogonal Space-Time Block Code,QSTBC)系统的性能,提出基于天线选择的QSTBC系统自适应设计方案,对QSTBC的编码结构添加自适应系数,使信道矩阵正交化,消除码间串扰.推导了系统的瞬时输出信噪比,以此作为天线选择准则.仿真结果表明,相对于未经过自适应编码设计的天线选择QSTBC系统,新系统的误码率性能有明显改善.     

GPS-RTK技术在铁路测量中的应用

介绍RTK技术应用于铁路定测的基本方法和步骤,通过应用实例证实了该技术的可行性和优越性。实践证明这种作业方法能够省掉不必要的中间环节,最大限度地减少外业工作量,从而缩短整个勘测工期。     

SNS柔性防护技术在边坡危岩防护中的应用

SNS柔性防护系统具有施工快捷、方便、环保、美观等独特的优势,应用于庐江至铜陵高速公路边坡危岩防护中．替代传统的加固防护措施,解决了在山区复杂环境地质条件下传统防护措施施工困难、进展缓慢等难题。     

拱形基板微带贴片天线性能分析

提出了一种新型微带贴片天线,对不同角度下天线的反射损耗、带宽和方向图进行了仿真.与普通微带贴片天线相比,这种新型天线的相对阻抗带宽(S11衰减到-10dB)一般在20%以上,个别角度下能达到43%,而且方向图有较大变化.     

基于罗兰C的UUV浅海导航定位技术研究

罗兰C工作于长波波段,具有一定的海水穿透能力,为UUV的水下导航定位提供了途径。在设计并实现罗兰C全向磁天线的基础上,通过对罗兰C信号传播场分量的分析,认为水下采用磁天线接收水平磁场信号是UUV的最佳选择,在此基础上,结合场强预测的布雷默曲线和水中信号衰减规律,仿真计算了罗兰C信号在不同距离、深度上的磁场场强和水下磁天线所能感应的电压值。利用所设计的磁天线,开展了水下接收罗兰C磁信号的实验,结果表明在表层水域(深度小于5米时),UUV利用罗兰C进行定位导航是可行的。     

基于扩展卡尔曼滤波的GPS信号跟踪技术

提出一种基于扩展卡尔曼滤波的GPS信号跟踪方法,通过扩展卡尔曼滤波器,得到基于相干积分支路的滤波模型,有效地削弱常规GPS跟踪环路中的跟踪误差,增强接收机的抗干扰性能,提升其在信号较弱位置下环路的跟踪性能,对加入惯性信息条件下惯性信息对系统所产生的影响做了相应的分析研究。通过仿真对比结果可以知道:当处于弱信号条件时,与通常用到的GPS信号跟踪方式相比,基于扩展卡尔曼滤波的信号跟踪算法可以有效提升跟踪的精度。     

Aggregating mobile object trajectories: cumulative time geographic density estimation for GPS data

We present new approaches that expand upon the time geographic density estimation (TGDE) framework previously employed to estimate potential path trees. In the past, TGDE metrics have identified possible locations an individual moving object may have passed between, given known origin and destination points. This paper utilizes a new form of TGDE to investigate taxicab GPS traces over a specified time horizon with position ‘gaps’. To this end, we propose a new extension to the TGDE framework, TGDE-C, which is used to determine the cumulative TGDE values for a group of GPS traces, at a given location. These metrics are applied to multiple taxis and allow for time of day analysis. Additionally, we combine these new extensions with existing TGDE metrics that allow us to determine how accessible individual or groups of vehicles are to urban opportunities.     

Developing an enhanced weight-based topological map-matching algorithm for intelligent transport systems

Map-matching (MM) algorithms integrate positioning data from a Global Positioning System (or a number of other positioning sensors) with a spatial road map with the aim of identifying the road segment on which a user (or a vehicle) is travelling and the location on that segment. Amongst the family of MM algorithms consisting of geometric, topological, probabilistic and advanced, topological MM (tMM) algorithms are relatively simple, easy and quick, enabling them to be implemented in real-time. Therefore, a tMM algorithm is used in many navigation devices manufactured by industry. However, existing tMM algorithms have a number of limitations which affect their performance relative to advanced MM algorithms. This paper demonstrates that it is possible by addressing these issues to significantly improve the performance of a tMM algorithm. This paper describes the development of an enhanced weight-based tMM algorithm in which the weights are determined from real-world field data using an optimisation technique. Two new weights for turn-restriction at junctions and link connectivity are introduced to improve the performance of matching, especially at junctions. A new procedure is developed for the initial map-matching process. Two consistency checks are introduced to minimise mismatches. The enhanced map-matching algorithm was tested using field data from dense urban areas and suburban areas. The algorithm identified 96.8% and 95.93% of the links correctly for positioning data collected in urban areas of central London and Washington, DC, respectively. In case of suburban area, in the west of London, the algorithm succeeded with 96.71% correct link identification with a horizontal accuracy of 9.81 m (2σ). This is superior to most existing topological MM algorithms and has the potential to support the navigation modules of many Intelligent Transport System (ITS) services.