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形变强度与地壳变形分析

本文利用GNSS等观测所获得的地壳位移速度结果并应用数值逼近理论, 提出了具有解析式的形变强度分析与计算方法。 根据形变的性质或类型将它们分别定义为形变强度、 水平形变强度、 水平剪切形变强度、 水平张压形变强度、 垂直剪切形变强度。 文中最后以GNSS 1999—2007年观测数据所产生的运动结果为例, 分析了川滇地区的地壳运动和形变, 并给出了不同性质形变强度的空间变化结果。     

Wide area real time kinematic decimetre positioning with multiple carrier GNSS signals

This paper presents the technical basis for wide area real time decimetre positioning services using multiple carrier signals transmitted by future GNSS such as modernized GPS and Compass systems. The first step is to form two ionosphere-reduced extra-widelanes (EWL) that have the minimal total noise levels in cycles, considering the effects of the ionospheric and tropospheric delays, orbital error, and phase noise terms in various observational environments. The proposed three carrier ambiguity resolution ...     

基于高频GNSS的2014年于田MS7.3级地震的同震位移研究

After the Yutian M_S7.3 earthquake,the authors instantly collected 1Hz high frequency data of the 4 reference stations within 350 km around the epicenter,and calculated the GNSS data with the TRACK module. The results showed that:( 1) The co-seismic displacement of Yutian station,about 54 km from the epicenter,is the most obvious,particularly in the EW component,with a change of about 52.5 ± 11mm,which is more than three times the mean-square error of calculating precision.( 2) In the Yutian reference station,the biggest variation in the EW component appeared within 1 minute after the earthquake.( 3) The change in the NS component is not great.     

求解模型对欧拉矢量的影响

利用GNSS水平运动场求解欧拉矢量时,待估参数的个数会对欧拉矢量结果产生影响,针对该问题本文分别从理论推导和具体算例角度进行了分析.首先从理论上推导出不同的求解模型得到的欧拉矢量的差异;然后以2004 ～2007年中国大陆GNSS水平运动场为基础,选用两种常用的求解模型(块体整体旋转模型和块体的整体旋转与均匀应变模型),讨论了求解模型对欧拉矢量及后续研究的影响.结果表明,两种模型下块体整体旋转的差异最大可达2.60mm·a-1,是不能忽略的.因此认为选用不同的块体运动模型会得到不同的地壳水平运动图像,在地壳水平运动分析中对此需加以重视.     

Using neural networks for calibration of time-domain reflectometry measurements

Abstract

Time-domain reflectometry (TDR) is an electromagnetic technique for measurements of water and solute transport in soils. The relationship between the TDR-measured dielectric constant (K_a ) and bulk soil electrical conductivity ([sgrave]_a) to water content (θ_W) and solute concentration is difficult to describe physically due to the complex dielectric response of wet soil. This has led to the development of mostly empirical calibration models. In the present study, artificial neural networks (ANNs) are utilized for calculations of θ_w and soil solution electrical conductivity ([sgrave]_w) from TDR-measured K_a and [sgrave]_a in sand. The ANN model performance is compared to other existing models. The results show that the ANN performs consistently better than all other models, suggesting the suitability of ANNs for accurate TDR calibrations.     

整体式GNSS接收机多路径效应分析

探讨了GNSS接收机天线多路径效应的计算和分析方法,分别运用由多路径计算原理编制的数据分析软件和TEQC软件处理整体式GNSS接收机获取的数据,并进行对比分析,其结果说明多路径效应的大小与高度角存在线性关系。在实际数据预处理中,可通过分析软件代替TEQC,简单方便地获得站点的多路径信息,对站点的数据评定提供有效的质量信息。     

江汉平原连续运行参考站网络系统建设

江汉平原连续运行参考站网络系统(JH-CORS)是以荆州市国土资源管理局土地勘测规划院GNSS站为系统控制中心,连接公安县、石首市、监利县、松滋市、洪湖市、仙桃市、潜江市、宜都市和嘉鱼县土地勘测规划院GNSS站的区域GNSS参考站系统。主要介绍了JH-CORS系统建设的主要内容、目标及项目建设的实施情况,供相关技术人员参考。     

双鸭山市连续运行卫星定位服务系统(SYS-CORS)暨南方NRS系统的建设及应用

论述了双鸭山市测绘行业对双鸭山市连续运行卫星定位服务系统(SYS-CORS)暨南方NRS系统的需求,介绍了系统建设过程,同时介绍了系统测试状况,最后叙述系统的功能、本系统的创新点及系统为社会提供信息服务的前景。     

Optimizing artificial neural network-based indoor positioning system using genetic algorithm

Abstract

The Global Positioning System (GPS) is expected to play an integral role in the development of digital earth; however, the GPS cannot provide positioning information in regions where a majority of the population spends their time, that is, in urban and indoor environments. Hence, alternate positioning systems that work in indoor and urban environments should be developed to achieve the vision of digital earth. Wi-Fi-based positioning systems (WPS) stand out because of the near-ubiquitous presence of the associated infrastructure and signals in indoor environments. The WPS-based fingerprinting is the most widely adopted technique for position determination, but its accuracy is lower than that of techniques such as time of arrival and angle of arrival. Improving the accuracy is still a challenging task because of the complex nature of the propagation of Wi-Fi signals. Here, a novel server-based, genetic-algorithm-optimized, cascading artificial neural network-based positioning model is presented. The model is tested in 2D and 3D indoor environments under varying conditions. The model is thoroughly investigated on a real Wi-Fi network, and its accuracy is found to be better than that of other well-known techniques. A mean accuracy of 1.9 m is achieved with 87% of the distance error within the range of 0–3 m.