测量控制网优化设计的可靠性准则法

测量控制网优化设计与网的精度、可靠性、灵敏度以及费用等准则有关,但这些准则之间的关系又十分密切,本文提出了一种基于观测值内部可靠性指标的测量控制网模拟法优化设计新方法,介绍了其原理和特点,并用实例说明了用该方法的计算步骤和优化效益。     

基于模糊神经网络的义县萤石成矿预测

成矿预测的模糊综合评判方法中评价因素权重确定时具有较强的人为因素,模糊神经网络方法可以建立在无模型基础上,自动获取输入与输出的关系,在专家确定权重初始值的情况下,通过网络训练确定出最优权重值,这在一定程度上减少了人为因素的影响.应用该方法对义县萤石成矿远景区进行了评价,其评价结果与实际一致.表明该方法可推广到其他区域、其他矿种的预测,但应根据预测对象的实际情况建立控矿因素集和相应的隶属度函数.     

GNSS three carrier ambiguity resolution using ionosphere-reduced virtual signals

This paper presents a general modeling strategy for ambiguity resolution (AR) and position estimation (PE) using three or more phase-based ranging signals from a global navigation satellite system (GNSS). The proposed strategy will identify three best “virtual” signals to allow for more reliable AR under certain observational conditions characterized by ionospheric and tropospheric delay variability, level of phase noise and orbit accuracy. The selected virtual signals suffer from minimal or relatively low ionospheric effects, and thus are known as ionosphere-reduced virtual signals. As a result, the ionospheric parameters in the geometry-based observational models can be eliminated for long baselines, typically those of length tens to hundreds of kilometres. The proposed modeling comprises three major steps. Step 1 is the geometry-free determination of the extra-widelane (EWL) formed between the two closest L-band carrier measurements, directly from the two corresponding code measurements. Step 2 forms the second EWL signal and resolves the integer ambiguity with a geometry-based estimator alone or together with the first EWL. This is followed by a procedure to correct for the first-order ionospheric delay using the two ambiguity-fixed widelane (WL) signals derived from the integer-fixed EWL signals. Step 3 finds an independent narrow-lane (NL) signal, which is used together with a refined WL to resolve NL ambiguity with geometry-based integer estimation and search algorithms. As a result, the above two AR processes performed with WL/NL and EWL/WL signals respectively, either in sequence or in parallel, can support real time kinematic (RTK) positioning over baselines of tens to hundreds of kilometres, thus enabling centimetre-to-decimentre positioning at the local, regional and even global scales in the future.     

The ionospheric eclipse factor method (IEFM) and its application to determining the ionospheric delay for GPS

A new method for modeling the ionospheric delay using global positioning system (GPS) data is proposed, called the ionospheric eclipse factor method (IEFM). It is based on establishing a concept referred to as the ionospheric eclipse factor (IEF) λ of the ionospheric pierce point (IPP) and the IEF’s influence factor (IFF) . The IEF can be used to make a relatively precise distinction between ionospheric daytime and nighttime, whereas the IFF is advantageous for describing the IEF’s variations with day, month, season and year, associated with seasonal variations of total electron content (TEC) of the ionosphere. By combining λ and with the local time t of IPP, the IEFM has the ability to precisely distinguish between ionospheric daytime and nighttime, as well as efficiently combine them during different seasons or months over a year at the IPP. The IEFM-based ionospheric delay estimates are validated by combining an absolute positioning mode with several ionospheric delay correction models or algorithms, using GPS data at an international Global Navigation Satellite System (GNSS) service (IGS) station (WTZR). Our results indicate that the IEFM may further improve ionospheric delay modeling using GPS data.     

基于AHP和BP神经网络的深部地热水可持续开发能力评价

采用资料完整性、开采潜力、回灌量、平均水压下降速率、地面沉降速率、水温、水质、地热井布局8项指标构建天津地热可持续开发能力评价指标体系;运用层次分析法确定了各项指标的权重,建立起评价因素集和评语集,给出了归一化数值;建立了天津地热可持续开发能力的BP神经网络模型,以层次分析法得出的结果作为样本,对BP网络进行了训练和测试,实例评价结果表明了AHP和BP神经网络方法的可行性,为地热资源的可持续开发能力评价提供了一种新的评价方法。     

基于神经网络方法的芦苇叶面积指数遥感反演

提出了一种从TM图像上获取芦苇冠层叶面积指数的方法:首先对芦苇的生长背景进行分类;然后,对不同的背景光谱利用冠层反射率(FCR)模型计算得到查找表;最后,利用实测数据和查找表中的数据作为参数进行BP神经网络模型训练,从而得到芦苇冠层LAI。结果表明,人工神经网络方法有很强的非线性拟合能力,能够消除背景对反演结果的影响,有效提高LAI反演的精度。     

区域似大地水准面确定的最小二乘支持向量机方法

支持向量机(SVM)是近年来发展起来的机器学习的新方法,它较好地解决小样本、非线性、高维数、局部极小点等实际问题.文中研究支持向量机的拓展算法--最小二乘支持向量机(LSSVM),并将其应用于确定大面积复杂似大地水准面.通过工程实例并与神经网络模型和二次曲面多项式拟合模型相比较,验证确定区域似大地水准面的LSSVM方法的有效性.     

模拟退火算法在控制网平差中的应用

线性最小二乘估计在对非线性函数进行线性近似的过程中会产生模型误差,而一些非线性参数估计方法可能因为函数复杂而难以求导,法方程系数矩阵秩亏或呈病态矩阵时难以求解,非线性迭代解法有时对初始值的选择存在依赖性,不恰当的初始值会导致迭代无法收敛。针对这些问题,引入了模拟退火算法,介绍了该算法的基本原理、计算步骤和收敛性,并以3个控制网平差应用为例,说明该算法具有无需求导求逆,简洁实用,易于编程等优势,并能实现全局优化,获得高精度的平差结果。     

基于多基站网络的VRS差分改正信息的方法分析

基于虚拟参考站VRS(Virtual Reference Stations)的GPS测量技术是近几年应用在网络RTK中的热门技术,文中首先介绍VRS的基本原理,然后利用站际星际二次差分技术,推导虚拟观测值,最后讨论研究虚拟参考站的双差改正数的内插算法。     

基于约束的城市街道网自动综合方法

近年来,基于约束的地图自动综合成为研究的热点。本研究在基于约束的地图自动综合理论的基础上,提出了一种城市街道网自动综合方法。该方法依赖于街道网综合中的约束和改进的动态决策树结构,它很好地将约束融入了特定的数据结构,实现了街道网的渐进式综合。实验证明了方法具备可行性。