城市高精度GPS控制网的复测与网形优化

针对布设的城市地铁GPS复测控制网，提出了地铁控制网复测的必要性。并在复测网形优化分析的基础上，讨论了起算点与地铁控制网不兼容性对精度的影响和筛选方法，实例表明此方法的有效性。     

地铁GPS控制网的布测与稳定性分析

简要介绍地铁GPS控制网设计、外业观测及数据处理情况,由于地铁建设周期较长,需要定期对控制网进行复测,详细介绍了控制网稳定性统计检验分析方法,并对控制网近4年复测数据进行了稳定性分析。     

港珠澳大桥首级控制网复测

介绍了港珠澳大桥首级控制网的复测方案,包括复测精度及网形设计、对控制网复测方法、技术要求及成果精度进行了介绍。最后,通过控制网复测成果和建网成果的比较,对首级控制网建网成果质量及控制点的稳定性进行了分析评价。     

城市高精度GPS控制网的复测与网形优化

针对布设的城市地铁GPS复测控制网,提出了地铁控制网复测的必要性.并在复测网形优化分析的基础上,讨论了起算点与地铁控制网不兼容性对精度的影响和筛选方法,实例表明此方法的有效性.     

轨道控制网平面网复测精度指标合理性探讨

轨道控制网(CPIII)是高速铁路无砟轨道铺设以及运营维护阶段的控制基准,高速铁路工程测量规范中关于CPIII平面网复测的精度指标是根据武广线的测量数据进行统计给出的,没有经过严密的理论推导。鉴于以上不足,对CPIII平面网复测精度指标进行了理论推导与研究,得出高铁规范中CPIII平面点复测与原测坐标较差,CPIII平面相邻点的复测与原测坐标增量较差两项指标的限差,这对评定CPIII控制点的稳定性、可靠性以及后续的施工和维护具有重要意义。     

某铁路工程控制网复测与稳定性分析

工程控制网是一切施工测量的基准,其稳定性直接关系到施工测量和工程的整体质量。因此,必须对控制网进周期性复测,以便分析控制网的稳定性。文章利用误差理论方法对复测成果进行了分析,得出了一些有益的结论和建议。     

长距离铁路隧道控制网复测及贯通测量误差分析

结合丛山峻岭中的长距离铁路隧道原有控制网的稳定性问题而开展本次复测工作,论述开展控制网复测的必要性,分析贯通测量误差值,着重对复测方法和精度指标进行探讨,提出一套长距离铁路隧道控制网的控制标准,可供以后使用时的依据与参考。     

高速公路控制网复测数据处理与稳定性分析

介绍了高速公路控制网复测技术方案,详细阐述了控制网复测数据处理的具体流程以及控制网成果质量评价,按照复测技术要求对控制点稳定性进行分析,对不稳定点的坐标进行修正更新,得到控制网最新坐标成果。     

马鞍山长江公路大桥施工控制网复测与分析

介绍了马鞍山长江公路大桥施工控制网复测情况,通过复测成果与原测成果的比较,结合现场施工及地形条件,分析了各控制点的稳定性,总结出施工控制网复测的技术方法和要点,实现了对该网后续复测、控制点加密及施工控制测量的指导。     

北京正负电子对撞机首级精密工程控制网测量

本文介绍了北京正负电子对撞机首级精密工程控制网的任务、网形设计、精度保证措施、实测方法和所达到的精度。还扼要地介绍了对撞机工程特殊情况下,控制点的埋设、投点、复测措施等情况。     

CORS系统网络安全策略

对CORS系统网络结构进行了分析,从网络结构和配置的角度,简述了防火墙控制、访问控制列表、主机等内容的安全策略。提出了通过移动专线APN为RTK用户提供服务的CORS安全措施,并给出了专线APN安全方案。     

Dynamic positioning configuration and its first-order optimization

Traditional geodetic network optimization deals with static and discrete control points. The modern space geodetic network is, on the other hand, composed of moving control points in space (satellites) and on the Earth (ground stations). The network configuration composed of these facilities is essentially dynamic and continuous. Moreover, besides the position parameter which needs to be estimated, other geophysical information or signals can also be extracted from the continuous observations. The dynamic (continuous) configuration of the space network determines whether a particular frequency of signals can be identified by this system. In this paper, we employ the functional analysis and graph theory to study the dynamic configuration of space geodetic networks, and mainly focus on the optimal estimation of the position and clock-offset parameters. The principle of the D-optimization is introduced in the Hilbert space after the concept of the traditional discrete configuration is generalized from the finite space to the infinite space. It shows that the D-optimization developed in the discrete optimization is still valid in the dynamic configuration optimization, and this is attributed to the natural generalization of least squares from the Euclidean space to the Hilbert space. Then, we introduce the principle of D-optimality invariance under the combination operation and rotation operation, and propose some D-optimal simplex dynamic configurations: (1) (Semi) circular configuration in 2-dimensional space; (2) the D-optimal cone configuration and D-optimal helical configuration which is close to the GPS constellation in 3-dimensional space. The initial design of GPS constellation can be approximately treated as a combination of 24 D-optimal helixes by properly adjusting the ascending node of different satellites to realize a so-called Walker constellation. In the case of estimating the receiver clock-offset parameter, we show that the circular configuration, the symmetrical cone configuration and helical curve configuration are still D-optimal. It shows that the given total observation time determines the optimal frequency (repeatability) of moving known points and vice versa, and one way to improve the repeatability is to increase the rotational speed. Under the Newton’s law of motion, the frequency of satellite motion determines the orbital altitude. Furthermore, we study three kinds of complex dynamic configurations, one of which is the combination of D-optimal cone configurations and a so-called Walker constellation composed of D-optimal helical configuration, the other is the nested cone configuration composed of n cones, and the last is the nested helical configuration composed of n orbital planes. It shows that an effective way to achieve high coverage is to employ the configuration composed of a certain number of moving known points instead of the simplex configuration (such as D-optimal helical configuration), and one can use the D-optimal simplex solutions or D-optimal complex configurations in any combination to achieve powerful configurations with flexile coverage and flexile repeatability. Alternately, how to optimally generate and assess the discrete configurations sampled from the continuous one is discussed. The proposed configuration optimization framework has taken the well-known regular polygons (such as equilateral triangle and quadrangular) in two-dimensional space and regular polyhedrons (regular tetrahedron, cube, regular octahedron, regular icosahedron, or regular dodecahedron) into account. It shows that the conclusions made by the proposed technique are more general and no longer limited by different sampling schemes. By the conditional equation of D-optimal nested helical configuration, the relevance issues of GNSS constellation optimization are solved and some examples are performed by GPS constellation to verify the validation of the newly proposed optimization technique. The proposed technique is potentially helpful in maintenance and quadratic optimization of single GNSS of which the orbital inclination and the orbital altitude change under the precession, as well as in optimally nesting GNSSs to perform global homogeneous coverage of the Earth.     

Improving neural network performance on the classification of complex geographic datasets

Neural Networks are now established computational tools used for search minimisation and data classification. They offer some highly desirable features for landuse classification problems since they are able to take in a variety of data types, recorded on different statistical scales, and combine them. As such, neural networks should offer advantages of increased accuracy. However, a barrier to their general acceptance and use by all but `experts' is the difficulty of configuring the network initially.  This paper describes the architectural problems of applying neural networks to landcover classification exercises in geography and details some of the latest developments from an ongoing research project aimed at overcoming these problems. A comprehensive strategy for the configuration of neural networks is presented, whereby the network is automatically constructed by a process involving initial analysis of the training data. By careful study of the functioning of each part of the network it is possible to select the architecture and initial weights on the node connections so the constructed network is `right first time'. Further adaptations are described to control network behaviour, to optimise functioning from the perspective of landcover classification. The entire configuration process is encapsulated by a single application which may be treated by the user as a `black box', allowing the network to the applied in much the same way as a maximum likelihood classifier, with no further effort being required of the user.     

GNSS精密控制网在特大型桥梁施工监测中的应用——以虎门二桥为例

以虎门二桥为例,介绍了全球卫星导航系统(GNSS)精密定位技术在特大型桥梁中的具体应用,在基线解算时,通过提高概略坐标精度、选择合适的解算策略、合理的约束条件等提高控制网解算精度,使得控制网成果的各项精度指标满足要求．对虎门二桥8期测量成果的统计,进一步验证了控制网的测量精度,通过对部分点位坐标较差的计算,统计了点位的具[JP2]体变动情况,采用单点检验法评定了控制点的稳定性,为其他类似跨海工程控制网提供了参考.      

一种高分辨率遥感影像建筑物自动检测方法

高分辨率遥感影像具有丰富的空间信息、地物几何结构和纹理信息,有助于对地物目标进行认知和解译。而建筑物目标在人类活动区域内占据重要地位,对高分辨率遥感影像中的建筑物进行自动检测具有重大意义。提出了一种基于全卷积神经网络的建筑物自动检测方法,并制作了建筑物样本数据集,利用基于区域的全卷积神经网络和特征检测网络进行建筑物检测模型的参数训练,对待检测影像进行预处理之后利用模型进行建筑物检测,得到影像中的建筑物目标的具体位置和类别置信度。实验证明,提出的检测方法具有更好的效果和更快的速度。检测召回率达到92%,检测准确率达到98%,证明了该方法针对建筑物检测具有较高的精度和较强的稳定性。     

基准点的组合后验方差检验法及应用

在大型工程中,定期分析控制网基准点的稳定性十分必要。介绍组合后验单位权检验对已知基准点进行稳定性分析的方法,并在三峡大坝的升船机控制网复测中得到实际应用,收到良好的效果。     

遗传神经网络在大坝安全评价中的应用

利用神经网络方法评价大坝安全具有一定的优势,但传统大坝安全评价方法不能为神经网络模型提供合适的学习样本。文中引入安全度值的概念,为神经网络提供可量化的学习样本,并针对BP神经网络收敛速度慢、稳定性差、易陷入局部极小等问题,利用遗传算法进行改进,提出基于遗传神经网络的大坝安全评价方法。工程实例表明,评价方法合理、可行。     

基于T-S模糊神经网络的变形预报研究

T-S模糊神经网络模型是根据模糊系统和人工神经网络优缺点具有明显的互补性结合而成。文中基于T-S模糊神经网络,将其应用于变形预测。通过实测数据和仿真数据分析比较了其与BP神经网络、小波神经网络在预测精度、算法稳定性和有效区间3个评价标准上的优劣。结果表明,在变形预测,特别是利用长周期监测数据进行预报时,T-S模糊神经网络具有一定的优势。     

基于坐标转换的高铁平面精测网复测稳定性分析方法探讨

首先介绍了现有各级平面精测网复测稳定性分析的常规方法,然后结合GRP网中判别CPⅢ点稳定性的方法,尝试使用三参数坐标转换进行高铁平面精测网复测稳定性分析,最后以某高铁CPI控制网实测数据为例进行分析。结果表明,不能完全使用三参数坐标转换代替常规方法进行精测网的稳定性分析,但可在使用坐标转换后的点位残差进行稳定性评价时,结合常规法进行综合分析,可提高常规法分析判别效率。     

新型GPS控制网布设及应用

设计出一种新型GPS控制网,通过与其他类型控制网进行比较分析,获得该新型GPS网的一些特点,并将该新型GPS控制网应用于工程实际中,实践表明:该新型GPS网,无论平面精度还是高程精度都高于设计精度,能够满足多种工程测量需要,值得借鉴。