一种基于三角网扩张法的Delaunay三角网逐块归并算法

本文中提出一种基于三角网扩张法的不规则三角网的逐块归并算法,它采用按横向或纵向对离散点集切割分块,对各子块用三角网扩张法构建Delaunay三角网,最后用三角网扩张法依次将相邻的子网合并。该算法采用的子集分块的做法使构网时的搜索范围减小,在数据量较大时避免了计算时间随点数的指数次增加,同时在构网时也能保证三角形邻接关系的正确维护。     

一种网格拓扑关系的三角网切割算法

针对目前的三角网切割效率不高的问题,该文提出了一种网格拓扑关系搜索的三角网模型切割方法。利用三角网模型中三角形的索引和顶点索引,构建边的索引,从而构建点索引、边索引和三角形索引之间的拓扑关系,最终形成三维模型的"边-顶点-邻接三角形的拓扑关系"。根据当前屏幕范围,提取三维视景体内的三角形,利用GPU并行运算,快速获取离视点最近的三角形索引,从而获取到所有三角网中的第一层三角网,并根据拓扑关系提取边界三角形,再利用基于边的约束对边界三角形进行重新剖分。实验结果表明,该方法可以快速准确地完成离视点最近的三角网模型表面的切割。     

L1-norm pre-analysis measures for geodetic networks

 Several pre-analysis measures which help to expose the behavior of L ₁ -norm minimization solutions are described. The pre-analysis measures are primarily based on familiar elements of the linear programming solution to L ₁-norm minimization, such as slack variables and the reduced-cost vector. By examining certain elements of the linear programming solution in a probabilistic light, it is possible to derive the cumulative distribution function (CDF) associated with univariate L ₁-norm residuals. Unlike traditional least squares (LS) residual CDFs, it is found that L ₁-norm residual CDFs fail to follow the normal distribution in general, and instead are characterized by both discrete and continuous (i.e. piecewise) segments. It is also found that an L ₁ equivalent to LS redundancy numbers exists and that these L ₁ equivalents are a byproduct of the univariate L ₁ univariate residual CDF. Probing deeper into the linear programming solution, it is found that certain combinations of observations which are capable of tolerating large-magnitude gross errors can be predicted by comprehensively tabulating the signs of slack variables associated with the L ₁ residuals. The developed techniques are illustrated on a two-dimensional trilateration network. Received: 6 July 2001 / Accepted: 21 February 2002     

大地问题中截面椭圆弧长的改进算法

为了避免大椭圆弧长算法中需要对球面方位角和极距角进行繁琐的象限判断问题,该文通过空间向量分析和椭球几何关系推导,给出了一种计算简洁、具有通用性的截面椭圆弧长算法。算例分析表明,该算法可以满足椭球面上两点间大地距离计算的应用需要,当大地距离小于2000km时,求得的截面椭圆弧长与较严密公式求得的大地线长的误差仅为厘米级。     

Deformations of geodetic networks in gravity-invariant and potential-invariant representations

The analysis of deformations and reductions of the geodetic networks in general gravity-invariant and potential-invariant representations of the actual gravity field of the Earth by normal (theoretical) gravity field has been presented. It has been shown that the linearized formulae of the scale factor and linearized formulae of the transformed azimuth and zenith distance induce the conformal character of transformation of three-dimensional networks in isozenithal-type of gravity-invariant representation. In isozenithal-type of gravity-invariant and potential-invariant representations the two-dimensional (horizontal) networks are transformed conformally. In isoparametric cases of gravity-invariant and potential-invariant representations, the two-dimensional networks are transformed equivalently with respect to the scale and angles, but non-conformally.     

Strength of long lines in terrestrial geodetic control networks

a knowledge of the à posteriori accuracy of long lines in classical triangulation networks is important not only for establishing the quality of existing primary national control networks, but also for assessing the likely contribution of satellite derived observations. Extensive tests carried out with various networks, ranging from a basic triangulation chain to Block VI of the European Triangulation Network, show definite trends. The à posteriori standard errors of both the scale and the orientation of an adjusted line diminish considerably as the length of the line increases. In the case of medium sized countries, the results compare favourably with those predicted for satellite derived data. The conclusions emphasize the need for great care in the reduction of terrestrial observations and the elimination of all possible systematic errors before proceeding with a least squares adjustment.     

Effect of heteroscedasticity and heterogeneousness on outlier detection for geodetic networks

The robustness of an outlier detection method strongly depends on the weights of observations, i.e., the type of the stochastic model applied (homoscedasticity, heteroscedasticity and heterogeneousness). In this paper, we have investigated how the reliability of the robust methods and tests for outliers changes depending on the weights of the observations in geodetic networks. Furthermore, the contribution of the directions and distances to horizontal control network with regard to reliability are investigated separately. The concept of a breakdown point is used as a global measure of robustness against outliers. The mean success rate (MSR) is found to be a practical tool for confirming the breakdown point. Many different “good” data samples are generated for each network and then deliberately contaminated using a Monte-Carlo simulation. Six robust methods and Baarda’s test are applied to the corrupted samples and the degree of corruption is varied. The performance of each method is measured using both local and global MSRs. Our research shows: (1) The MSRs of Baarda’s test change depending on the strength of the heteroscedasticity, but do not change for trilateration and leveling networks, (2) the global MSRs of robust methods do not differ considerably from the local ones     

Rigorous mathematical models for the densification and integration of geodetic networks

Existing position information in a network can be integrated with the densification solution in two ways: One way is to obtain a solution of the densification network followed by a merger of this and all other solutions or vice versa. Alternatively, the existing solutions (not used as weighted constraints) can be taken to be pseudo-observations in a simultaneous adjustment with the “new” observations. In both cases, all existing solutions must first be transformed to the coordinate system of the densified network and be statistically compatible with it. Simultaneous densification and integration is discussed through mathematical adjustment models in which the geometrical strength of networks is underscored. The rationale behind densifying and integrating networks either in two different steps or simultaneously is analyzed. It is concluded that the simultaneous approach should be avoided unless the various solutions turn out to be statistically compatible.     

Comparison of reliability and geometrical strength criteria in geodetic networks

 The proper and optimal design and subsequent assessment of geodetic networks is an integral part of most surveying engineering projects. Optimization and design are carried out before the measurements are actually made. A geodetic network is designed and optimized in terms of high reliability and the results are compared with those obtained by the robustness analysis technique. The purpose of an optimal design is to solve for both the network configuration (first-order design) and observations accuracy (second-order design) in order to meet the desired criteria. For this purpose, an analytical method is presented for performing the first-order design, second-order design, and/or the combined design. In order to evaluate the geometrical strength of a geodetic network, the results of robustness analysis are displayed in terms of robustness in rotation, robustness in shear, and robustness in scale. Results showed that the robustness parameters were affected by redundancy numbers. The largest robustness parameters were due to the observations with minimum redundancy numbers. Received: 14 August 2000 / Accepted: 2 January 2001     

A statistical filter for geodetic observations

A method for filtering of geodetic observationwhich leaves the final result normally distributed, is presented. Furthermore, it is shown that if you sacrifice100.a% of all the observations you may be (1−β).100% sure that a gross error of the size Δ is rejected. Another and, may be intuitively, more appealing method is presented; the two methods are compared and it is shown why Method 1 should be preferred to Method 2 for geodetic purposes. Finally the two methods are demonstrated in some numerical examples.     

针对复杂道路网络的车辆轨迹地图匹配算法

针对高度城市化地区存在的复杂道路网络环境下,如何高效地进行车辆轨迹数据的地图匹配问题,该文提出了一种针对复杂道路网络的车辆轨迹数据地图匹配算法。该算法以车辆轨迹序列为匹配对象,通过环形轨迹的识别把车辆轨迹序列划分为无环路轨迹段,并用道路拓扑关系来计算轨迹序列的最优匹配路线,实现在复杂道路网络中的车辆轨迹数据地图匹配。为了验证本算法的性能,以上海市道路网络为实验区,以约1.3万辆出租车在2015年4月的轨迹数据为数据源,进行实证研究。实验结果显示,该文提出的地图匹配算法在复杂的道路网络中有较高的匹配成功率和匹配效率。     

GPS vector configuration design for monitoring deformation networks

 The performance of geodetic monitoring networks is heavily influenced by the configuration of the measured GPS vectors. As an effective design of the GPS measurements will decrease GPS campaign costs and increase the accuracy and reliability of the entire network, the identification of the preferred GPS vectors for measurement has been highlighted as a core problem in the process of deformation monitoring. An algorithm based on a sensitivity analysis of the network, as dependent upon a postulated velocity field, is suggested for the selection of the optimal GPS vectors. Relevant mathematical and statistical concepts are presented as the basis for an improved method of vector configuration design. A sensitivity analysis of the geodetic geodynamic network in the north of Israel is presented, where the method is examined against two deformation models, the Simple Transform Fault and the Locked Fault. The proposed method is suggested as a means for the improvement of the design of monitoring networks, a common practice worldwide. Received: 30 July 2001 / Accepted: 3 June 2002 Acknowledgments. It is my pleasant duty to thank the Survey of Israel and Dr. E. Ostrovsky for providing the variance–covariance matrix of the G1 network in northern Israel. I would like to thank the reviewers of this paper for their constructive and helpful remarks.     

Applications of graph theory to gross error detection for GPS geodetic control networks

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Applications of graph theory to gross error detection for GPS geodetic control networks

This paper describes a broad perspective of the application of graph theory to establishment of GPS control networks whereby the GPS network is considered as a connected and directed graph with three components. In this algorithm the gross error detection is undertaken through loops of different spanning trees using the “Loop Law” in which the individual components ΔX, ΔY and ΔZ sum up to zero. If the sum of the respective vector components ΩX, ΩY and ΩZ in a loop is not zero and if the error is beyond the tolerable limit (ε>ω), it indicates the existence of gross errors in one of the baselines in the loop and therefore the baseline must be removed or re-observed. After successful screening of errors by graph theory, network adjustment can be carried out. In this paper, the GPS data from the control network established as refence system for the HP Dam at Baishan county in Liaoning province is presented to illustrate the algorithm.     

一种地类图斑符号配置算法

地图符号配置是地图可视化的重要组成部分,传统的土地利用现状图制图中,地类图斑的符号化通过填充法或填绘法实现,但是这些方法不能解决符号的空间冲突问题。本文从地图认识的角度出发,归纳地类图斑的符号化规则,提出了一种地类符号配置算法,并利用C#语言、Arc Engine开发接口实现了该算法。实验结果表明,算法较好解决了地类符号与其他地物要素压盖问题。     

A fill-in storage technique for geodetic normal equations

A minimum fill-in scheme, published by Yale University and not previously discussed in the geodetic literature, has been tested on four typical triangulation networks. Its computer storage requirement has been compared with that of the profile method using Snay's station reordering algorithm. Tests have been carried out for terrestrial and mixed terrestrial/satellite networks. The conclusion is that the fill-in scheme is a viable method for geodetic networks and, in some cases, it needs less computer storage than the profile method.     

Optimum estimation in a growth curve model with a priori unknown variance components in geodetic networks

Summary Time varying coordinates of points of a geodetic network are indirectly measured by a group of measurement devices with different characteristics of accuracy in several epochs. The design of the measurement is the same in all epochs. The ratio of the characteristics of accuracy is a priori unknown. The aim is to determine an estimator of the parameters of functions modelling changes of the coordinates, confidence regions of these functions and to construct a procedure for testing linear hypotheses on time varying coordinates of a geodetic network. As the characteristics of accuracy are a priori unknown, the problem of their estimation has to be solved simultaneously. The research of rules of recent crustal movements leads to studying the mentioned model.     

A new triple-frequency cycle slip detecting algorithm validated with BDS data

Triple-frequency global navigation satellite systems allow the introduction of additional linear observation combinations. We define two geometry-free phase combinations and one geometry-free pseudorange minus phase linear combination to detect and correct cycle slip in real time. At first, the optimal BDS (BeiDou System) triple-frequency geometry-free phase combinations are selected for cycle slip detection. Then, a detailed analysis of the cycle slip detection is performed by examining whether some special cycle slip groups cannot be discovered by the selected combinations. Since there still remain some cycle slip groups undetectable by the two geometry-free phase combinations, we add a pseudorange minus phase linear combination which is linearly independent with these two phase combinations, to be sure that all the cycle slips can be detected. After that, an effective decorrelation search based on LAMBDA and least squares minimum principle is applied to calculate and determine the cycle slips. The method has been tested on triple-frequency undifferenced BDS data coming from a benign observation environment. Results show that the proposed method is able to detect and repair all the small cycle slips in the three carriers.