scholarly journals Adjustment of an Integrated Geodetic Network Composed of GNSS Vectors and Classical Terrestrial Linear Pseudo-Observations

2021 ◽  
Vol 11 (10) ◽  
pp. 4352
Author(s):  
Tadeusz Gargula

The paper proposes a new method for adjusting classical terrestrial observations (total station) together with satellite (GNSS-Global Navigation Satellite Systems) vectors. All the observations are adjusted in a single common three-dimensional system of reference. The proposed method does not require the observations to be projected onto an ellipsoid or converted between reference systems. The adjustment process follows the transformation of a classical geodetic network (distances and horizontal and vertical angles) into a spatial linear (distance) network. This step facilitates easy integration with GNSS vectors when results are numerically processed. The paper offers detailed formulas for calculating pseudo-observations (spatial distances) from input terrestrial observations (horizontal and vertical angles, horizontal distances, height of instrument and height of target). The next stage was to set observation equations and transform them into a linear form (functional adjustment model of geodetic observations). A method was provided as well for determining the mean errors of the pseudo-observations, necessary to assess the accuracy of the values following the adjustment (point coordinates). The proposed algorithm was verified in practice whereby an integrated network made up of a GNSS vector network and a classical linear-angular network was adjusted.

Sensors ◽  
2019 ◽  
Vol 19 (20) ◽  
pp. 4535 ◽  
Author(s):  
Ismael Érique Koch ◽  
Ivandro Klein ◽  
Luiz Gonzaga ◽  
Marcelo Tomio Matsuoka ◽  
Vinicius Francisco Rofatto ◽  
...  

Geodetic networks provide accurate three-dimensional control points for mapping activities, geoinformation, and infrastructure works. Accurate computation and adjustment are necessary, as all data collection is vulnerable to outliers. Applying a Least Squares (LS) process can lead to inaccuracy over many points in such conditions. Robust Estimator (RE) methods are less sensitive to outliers and provide an alternative to conventional LS. To solve the RE functions, we propose a new metaheuristic (MH), based on the Vortex Search (IVS) algorithm, along with a novel search space definition scheme. Numerous scenarios for a Global Navigation Satellite Systems (GNSS)-based network are generated to compare and analyze the behavior of several known REs. A classic iterative RE and an LS process are also tested for comparison. We analyze the median and trim position of several estimators, in order to verify their impact on the estimates. The tests show that IVS performs better than the original algorithm; therefore, we adopted it in all subsequent RE computations. Regarding network adjustments, outcomes in the parameter estimation show that REs achieve better results in large-scale outliers’ scenarios. For detection, both LS and REs identify most outliers in schemes with large outliers.


2020 ◽  
Author(s):  
Kelly Brunt ◽  
Robert Hawley

<p>The Greenland Geodetic Network (GNET) consists of 58 global navigation satellite systems (GNSS) installed on the bedrock around the perimeter of the island. Much of the network was installed between 2007 and 2009, providing a long time series of GNSS data for much of Greenland. The network is currently owned and maintained by the Danish Agency for Data Supply and Efficiency (SDFE), while the National Science Foundation (NSF) provides support for data transport from the deep field. Here, we present a new resource (go-gnet.org) intended to be a clearinghouse to foster international collaborations and to encourage new and innovative use of these data.</p>


2017 ◽  
Vol 71 (1) ◽  
pp. 1-20 ◽  
Author(s):  
Mounir Adjrad ◽  
Paul D. Groves

In dense urban areas, conventional Global Navigation Satellite Systems (GNSS) positioning can exhibit errors of tens of metres due to the obstruction and reflection of the signals by the surrounding buildings. By using Three-Dimensional (3D) mapping of the buildings, the accuracy can be significantly improved. This paper demonstrates the first integration of GNSS shadow matching with 3D-mapping-aided GNSS ranging. The integration is performed in the position domain, whereby separate ranging and shadow matching position solutions are computed, then combined using direction-dependent weighting. Two weighting strategies are compared, one based on the computation of ranging-based and shadow matching position error covariance matrices, and a deterministic approach based on the street azimuth. Using experimental data collected from a u-blox GNSS receiver, it is shown that both integrated position solutions are significantly more accurate than either shadow matching or 3D-mapping-aided ranging on their own. The overall Root Mean Square (RMS) horizontal accuracy obtained using covariance-based weighting was 6·1 m, a factor of four improvement on the 25·9 m obtained using conventional GNSS positioning. Results are also presented using smartphone data, where shadow matching is integrated with conventional GNSS positioning.


2017 ◽  
Vol 35 (2) ◽  
pp. 203-215 ◽  
Author(s):  
Tatjana Gerzen ◽  
Volker Wilken ◽  
David Minkwitz ◽  
Mainul M. Hoque ◽  
Stefan Schlüter

Abstract. The reliable estimation of ionospheric refraction effects is an important topic in the GNSS (Global Navigation Satellite Systems) positioning and navigation domain, especially in safety-of-life applications. This paper describes a three-dimensional ionosphere reconstruction approach that combines three data sources with an ionospheric background model: space- and ground-based total electron content (TEC) measurements and ionosonde observations. First the background model is adjusted by F2 layer characteristics, obtained from space-based ionospheric radio occultation (IRO) profiles and ionosonde data, and secondly the final electron density distribution is estimated by an algebraic reconstruction technique.The method described is validated by TEC measurements of independent ground-based GNSS stations, space-based TEC from the Jason 1 and 2 satellites, and ionosonde observations. A significant improvement is achieved by the data assimilation, with a decrease in the residual errors by up to 98 % compared to the initial guess of the background. Furthermore, the results underpin the capability of space-based measurements to overcome data gaps in reconstruction areas where less GNSS ground-station infrastructure exists.


2020 ◽  
Vol 1 (2) ◽  
Author(s):  
Luu ANH TUAN ◽  
Hoang NGOC HA ◽  
La PHU HIEN ◽  
Pham VAN CHUNG

Recently, in Vietnam, the detection of geodetic measurements that contain rough errors as well as such data processing method has been considered as a key step in geodetic data processing, especially for large geodetic networks with many different types of measurements like 3D - Global Navigation Satellite Systems (GNSS) network. On the other hand, mines in Vietnam often have complex terrains, so it is necessary to apply modern and flexible surveying methods in combination with ground and space measurements to build 3D coordinates control networks for management and exploitation to ensure sustainable development. Therefore, this research developed a Robust estimation method based on empirical weighting function for establishing 3D geodetic network combining terrestrial observation and GNSS vectors. The experiment on processing the combined network in Lang Son limestone quarry, Vietnam showed that the proposed method could be an effective solution for processing 3D terrestrial – GNSS geodetic network for mine surveying in Vietnam.


Author(s):  
Aleksandr Suchilin ◽  
Nadezhda Belay ◽  
Ivan Voskresensky ◽  
Svetlana Mikheeva ◽  
Victoria Zorina ◽  
...  

The method of studying the abrasion-accumulative coast of the Western coast of Crimea within the urban area of Sevastopol includes remote sensing using unmanned aerial vehicles (UAVs) and field studies of the morphology and structure of abrasion and landslide landforms of the coast. As a result of the research, the morphological zoning of the abrasion-accumulative coast was established. The formation of the morphological zoning of the abrasion-accumulative coast (according to I.S. Shchukin) during the last 150 years took place at a constant level of the Black Sea. Analysis of the coast from previously published multi-temporal maps and aerospace photographs revealed different stages in the movement of the coastline and landslide scarp. Since 1966, the coastal area has been used for low-rise residential development, which may have influenced the activity of landslide processes in the coastal strip. Remote sensing using UAVs consists of aerial photography of the research area along the planned flight route at altitudes of 20–100 m, with further compilation of a large-scale orthophotomap from a mosaic of images with geospatial fixation of images to the signs of the reference long-term local geodetic network, previously measured by the methods of global navigation satellite systems (GNSS ), as well as the formation of a digital elevation model (DEM) and the compilation of derived maps and plans on its basis in the environment of geographic information systems (GIS), for the analysis of the morphometry of the relief and modeling. The developed method of remote sensing of the Earth with the use of UAVs and simultaneous field studies makes it possible to organize operational monitoring of dynamically developing abrasion-accumulative shores.


2018 ◽  
Vol 36 (5) ◽  
pp. 1255-1266
Author(s):  
Sicheng Wang ◽  
Sixun Huang ◽  
Hanxian Fang

Abstract. Ionospheric tomography based on the total electron content (TEC) data along the ray path from Global Navigation Satellite Systems (GNSS) satellites to ground receivers is a typical ill-posed inverse problem. The regularization method is an effective method to solve this problem, which incorporates prior constraints to approximate the real ionospheric variations. When two or more prior constraints are used, the corresponding multiple regularization parameters are introduced in the cost functional. Assuming that the ionospheric spatial variations can be separable in the horizontal and vertical directions, different prior constraints are used in each direction, and the dual-parameter regularization algorithm is established to reconstruct the three-dimensional ionospheric electron density in the present paper. To make the reconstruction results comprehensively reflect the observation information and background (prior) information, it is crucial to determine the optimal regularization parameters. The linear model function method is used to choose these regularization parameters. Both an ideal test and a real test show that this regularization algorithm can effectively improve the background model output.


2021 ◽  
Vol 13 (16) ◽  
pp. 3056
Author(s):  
Si Xiong ◽  
Fujian Ma ◽  
Xiaodong Ren ◽  
Jun Chen ◽  
Xiaohong Zhang

Global navigation satellite systems (GNSS) water vapor tomography is an important technique to obtain the three-dimensional distribution of atmospheric water vapor. The rapid development of low Earth orbit (LEO) constellations has led to a richer set of observations, which brings new expectations for water vapor tomography. This paper analyzes the influence of LEO constellation-augmented multi-GNSS(LCAMG)on the tomography, in terms of ray distribution, tomography accuracy, and horizontal resolution, by simulating LEO constellation data. The results show that after adding 288 LEO satellites to GNSS, the 30-min ray distribution effect of GNSS can be achieved in 10 min, which can effectively shorten the observation time by 66.7%. In the 10-min observation time, the non-repetitive effective observation value of LCAMG is 2.38 times that of GNSS, and the accuracy is 1.27% higher than that of GNSS. Compared with GNSS and the global positioning system (GPS), at a horizontal resolution of 13 × 14, the proportion of empty voxels in LCAMG reduces by 5.22% and 22.53%, respectively.


2020 ◽  
Vol 12 (7) ◽  
pp. 1080
Author(s):  
Panagiotis Partsinevelos ◽  
Dimitrios Chatziparaschis ◽  
Dimitrios Trigkakis ◽  
Achilleas Tripolitsiotis

Global Navigation Satellite Systems (GNSS) are extensively used for location-based services, civil and military applications, precise time reference, atmosphere sensing, and other applications. In surveying and mapping applications, GNSS provides precise three-dimensional positioning all over the globe, day and night, under almost any weather conditions. The visibility of the ground receiver to GNSS satellites constitutes the main driver of accuracy for GNSS positioning. When this visibility is obstructed by buildings, high vegetation, or steep slopes, the accuracy is degraded and alternative techniques have to be assumed. In this study, a novel concept of using an unmanned aerial system (UAS) as an intermediate means for improving the accuracy of ground positioning in GNSS-denied environments is presented. The higher elevation of the UAS provides a clear-sky visibility line towards the GNSS satellites, thus its accuracy is significantly enhanced with respect to the ground GNSS receiver. Thus, the main endeavor is to transfer the order of accuracy of the GNSS on-board the UAS to the ground. The general architecture of the proposed system includes hardware and software components (i.e., camera, gimbal, range finder) for the automation of the procedure. The integration of the coordinate systems for each payload setting is described, while an error budget analysis is carried out to evaluate and identify the system’s critical elements along with the potential of the proposed method.


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