scholarly journals A Novel UAV-Assisted Positioning System for GNSS-Denied Environments

2020 ◽  
Vol 12 (7) ◽  
pp. 1080
Author(s):  
Panagiotis Partsinevelos ◽  
Dimitrios Chatziparaschis ◽  
Dimitrios Trigkakis ◽  
Achilleas Tripolitsiotis
Keyword(s):  
Three Dimensional ◽  
Weather Conditions ◽  
Location Based Services ◽  
Global Navigation Satellite Systems ◽  
Satellite Systems ◽  
Budget Analysis ◽  
Main Driver ◽  
Reference Atmosphere ◽  
Novel Concept ◽  
Global Navigation Satellite

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.

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
Keyword(s):  
Three Dimensional ◽  
Geodetic Network ◽  
Global Navigation Satellite Systems ◽  
Adjustment Process ◽  
Dimensional System ◽  
Integrated Network ◽  
Satellite Systems ◽  
Linear Distance ◽  
Easy Integration ◽  
Global Navigation Satellite

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.

scholarly journals Robust Estimators in Geodetic Networks Based on a New Metaheuristic: Independent Vortices Search

Sensors ◽  
2019 ◽  
Vol 19 (20) ◽  
pp. 4535 ◽  
Author(s):  
Ismael Érique Koch ◽  
Ivandro Klein ◽  
Luiz Gonzaga ◽  
Marcelo Tomio Matsuoka ◽  
Vinicius Francisco Rofatto ◽  
...  
Keyword(s):  
Large Scale ◽  
Three Dimensional ◽  
Search Space ◽  
Global Navigation Satellite Systems ◽  
Robust Estimator ◽  
Satellite Systems ◽  
Original Algorithm ◽  
Geodetic Networks ◽  
Global Navigation Satellite ◽  
Better Than

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.

scholarly journals LOCALIZATION CORRECTIONS FOR MOBILE LASER SCANNER USING LOCAL SUPPORT-BASED OUTLIER FILTERING

2016 ◽  
Vol III-4 ◽  
pp. 81-88 ◽  
Author(s):  
V. V. Lehtola ◽  
J.-P. Virtanen ◽  
P. Rönnholm ◽  
A. Nüchter
Keyword(s):  
Degrees Of Freedom ◽  
Laser Scanner ◽  
Three Dimensions ◽  
Global Navigation Satellite Systems ◽  
Dimensional Solution ◽  
Satellite Systems ◽  
Localization And Mapping ◽  
Local Support ◽  
Novel Concept ◽  
Global Navigation Satellite

Following the pioneering work introduced in [Lehtola et al., ISPRS J. Photogramm. Remote Sens. 99, 2015, pp. 25–29], we extend the state-of-the-art intrinsic localization solution for a single two-dimensional (2D) laser scanner from one into (quasi) three dimensions (3D). By intrinsic localization, we mean that no external sensors are used to localize the scanner, such as inertial measurement devices (IMU) or global navigation satellite systems (GNSS). Specifically, the proposed method builds on a novel concept of local support-based filtering of outliers, which enables the use of six degrees-of-freedom (DoF) simultaneous localization and mapping (SLAM) for the purpose of enacting appropriate trajectory corrections into the previous one-dimensional solution. Moreover, the local support-based filtering concept is platform independent, and is therefore likely to be widely generalizable. The here presented overall method is yet limited into quasi-3D by its inability to recover trajectories with steep curvature, but in the future, it may be further extended into full 3D.

scholarly journals Intelligent Urban Positioning: Integration of Shadow Matching with 3D-Mapping-Aided GNSS Ranging

2017 ◽  
Vol 71 (1) ◽  
pp. 1-20 ◽  
Author(s):  
Mounir Adjrad ◽  
Paul D. Groves
Keyword(s):  
Urban Areas ◽  
Three Dimensional ◽  
Covariance Matrices ◽  
Global Navigation Satellite Systems ◽  
3D Mapping ◽  
Deterministic Approach ◽  
Satellite Systems ◽  
Gnss Positioning ◽  
Error Covariance ◽  
Global Navigation Satellite

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.

scholarly journals Three-dimensional data assimilation for ionospheric reference scenarios

2017 ◽  
Vol 35 (2) ◽  
pp. 203-215 ◽  
Author(s):  
Tatjana Gerzen ◽  
Volker Wilken ◽  
David Minkwitz ◽  
Mainul M. Hoque ◽  
Stefan Schlüter
Keyword(s):  
Data Assimilation ◽  
Three Dimensional ◽  
Model Space ◽  
Initial Guess ◽  
Global Navigation Satellite Systems ◽  
Background Model ◽  
Electron Content ◽  
Total Electron ◽  
Satellite Systems ◽  
Global Navigation Satellite

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.

scholarly journals LOCALIZATION CORRECTIONS FOR MOBILE LASER SCANNER USING LOCAL SUPPORT-BASED OUTLIER FILTERING

2016 ◽  
Vol III-4 ◽  
pp. 81-88 ◽  
Author(s):  
V. V. Lehtola ◽  
J.-P. Virtanen ◽  
P. Rönnholm ◽  
A. Nüchter
Keyword(s):  
Degrees Of Freedom ◽  
Laser Scanner ◽  
Three Dimensions ◽  
Global Navigation Satellite Systems ◽  
Dimensional Solution ◽  
Satellite Systems ◽  
Localization And Mapping ◽  
Local Support ◽  
Novel Concept ◽  
Global Navigation Satellite

Following the pioneering work introduced in [Lehtola et al., ISPRS J. Photogramm. Remote Sens. 99, 2015, pp. 25–29], we extend the state-of-the-art intrinsic localization solution for a single two-dimensional (2D) laser scanner from one into (quasi) three dimensions (3D). By intrinsic localization, we mean that no external sensors are used to localize the scanner, such as inertial measurement devices (IMU) or global navigation satellite systems (GNSS). Specifically, the proposed method builds on a novel concept of local support-based filtering of outliers, which enables the use of six degrees-of-freedom (DoF) simultaneous localization and mapping (SLAM) for the purpose of enacting appropriate trajectory corrections into the previous one-dimensional solution. Moreover, the local support-based filtering concept is platform independent, and is therefore likely to be widely generalizable. The here presented overall method is yet limited into quasi-3D by its inability to recover trajectories with steep curvature, but in the future, it may be further extended into full 3D.

scholarly journals Dual-parameter regularization method in three-dimensional ionospheric reconstruction

2018 ◽  
Vol 36 (5) ◽  
pp. 1255-1266
Author(s):  
Sicheng Wang ◽  
Sixun Huang ◽  
Hanxian Fang
Keyword(s):  
Regularization Method ◽  
Three Dimensional ◽  
Global Navigation Satellite Systems ◽  
Electron Content ◽  
Regularization Algorithm ◽  
Total Electron ◽  
Satellite Systems ◽  
Regularization Parameters ◽  
Global Navigation Satellite ◽  
Parameter Regularization

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.

scholarly journals LEO Constellation-Augmented Multi-GNSS for 3D Water Vapor Tomography

2021 ◽  
Vol 13 (16) ◽  
pp. 3056
Author(s):  
Si Xiong ◽  
Fujian Ma ◽  
Xiaodong Ren ◽  
Jun Chen ◽  
Xiaohong Zhang
Keyword(s):  
Water Vapor ◽  
Rapid Development ◽  
Three Dimensional ◽  
Horizontal Resolution ◽  
Observation Time ◽  
Low Earth Orbit ◽  
Global Navigation Satellite Systems ◽  
Satellite Systems ◽  
Dimensional Distribution ◽  
Global Navigation Satellite

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.

scholarly journals The key role of GNSS for monitoring geodetic parameters of the Earth

2021 ◽  
pp. 10-15
Author(s):  
С.П. Кузин
Keyword(s):  
Weather Conditions ◽  
Signal Propagation ◽  
Global Navigation Satellite Systems ◽  
Navigation Systems ◽  
Microwave Range ◽  
Satellite Systems ◽  
Ground Segment ◽  
The Earth ◽  
Gnss Receivers ◽  
Global Navigation Satellite

Глобальные навигационные спутниковые системы (ГНСС) являются основным инструментом для контроля геодезических параметров Земли, построения и постоянного контроля земной системы отсчета и связи измерений различных спутниковых геодезических технологий. ГНСС состоят из наземного сегмента (приемники ГНСС) и орбитальной группировки (навигационные спутники системы). Микроволновый диапазон сигналов ГНСС позволяет использовать данные системы при любых погодных условиях, а двухчастотные несущие позволяют, в значительной степени, исключить ионосферную задержку распространения сигналов. Помимо выполнения основных геодезических определений навигационные системы также могут быть использованы для решения социальных и других позиционных измерений, требующих высокой точности. В данной статье автором рассмотрены основные задачи, решаемые ГНСС, определены требования к точности продуктов навигационных систем и приведены направления развития наземной и орбитальных частей ГНСС, учитывая потребности мирового геодезического сообщества. Global navigation satellite systems (GNSS) are a fundamental tool for monitoring geodesic parameters of the Earth, building and constantly monitoring the Earth’s reference system and connecting measurements of various satellite geodetic technologies. GNSS consist of a ground segment (GNSS receivers) and an orbital grouping (navigation satellites of the system). The microwave range of GNSS signals allows using these systems in all weather conditions, and the two-frequency carriers allow, to a large extent, eliminating the ionospheric delay of signal propagation. In addition to performing basic geodetic definitions, GNSS can also be used to solve social and other positional measurements that require high accuracy. In this article the author discusses the main tasks solved by GNSS, defines the requirements for the accuracy of navigation systems products, and provides directions for the development of the ground and orbital parts of GNSS taking into account the needs of the international geodetic community.

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