scholarly journals Design, Implementation and Validation of a GNSS Measurement Exclusion and Weighting Function with a Dual Polarized Antenna

Sensors ◽  
2018 ◽  
Vol 18 (12) ◽  
pp. 4483
Author(s):  
Daniel Egea-Roca ◽  
Antonio Tripiana-Caballero ◽  
José López-Salcedo ◽  
Gonzalo Seco-Granados ◽  
Wim De Wilde ◽  
...  
Keyword(s):  
Precision Agriculture ◽  
Time Management ◽  
Autonomous Vehicles ◽  
Weighting Function ◽  
Modern Society ◽  
Global Navigation Satellite Systems ◽  
Satellite Systems ◽  
Dual Polarized ◽  
Global Navigation Satellite ◽  
Dual Polarized Antenna

Global Navigation Satellite Systems (GNSSs) have become a ubiquitous tool for our modern society to carry out vital tasks such as transportation, civil engineering or precision agriculture. This breath has reached the realm of safety-critical applications such as time management of critical infrastructures or autonomous vehicles, in which GNSS is an essential tool nowadays. Unfortunately, current GNSS performance is not enough to fulfill the requirements of these professional and critical applications. For this reason, the FANTASTIC project was launched to boost the adoption of these applications. The project was funded by the European GNSS agency (GSA) in order to enhance the robustness and accuracy of GNSS in harsh environments. This paper presents the part related to the development of a weighting and exclusion function with a dual circularly polarized antenna. The idea is to reduce the effects of multipath by weighting and/or excluding those measurements affected by multipath. The observables and other metrics obtained from a dual polarized antenna will be exploited to define an exclusion threshold and to provide the weights. Real-world experiments will show the improvement in the positioning solution, using all available constellations, obtained with the developed technique.

scholarly journals Practical Modeling of GNSS for Autonomous Vehicles in Urban Environments

Sensors ◽  
2019 ◽  
Vol 19 (19) ◽  
pp. 4236
Author(s):  
Woosik Lee ◽  
Hyojoo Cho ◽  
Seungho Hyeong ◽  
Woojin Chung
Keyword(s):  
Motion Estimation ◽  
Autonomous Vehicles ◽  
Autonomous Navigation ◽  
Urban Environments ◽  
Global Navigation Satellite Systems ◽  
Navigation Satellite ◽  
Key Technology ◽  
Satellite Systems ◽  
Agricultural Robots ◽  
Global Navigation Satellite

Autonomous navigation technology is used in various applications, such as agricultural robots and autonomous vehicles. The key technology for autonomous navigation is ego-motion estimation, which uses various sensors. Wheel encoders and global navigation satellite systems (GNSSs) are widely used in localization for autonomous vehicles, and there are a few quantitative strategies for handling the information obtained through their sensors. In many cases, the modeling of uncertainty and sensor fusion depends on the experience of the researchers. In this study, we address the problem of quantitatively modeling uncertainty in the accumulated GNSS and in wheel encoder data accumulated in anonymous urban environments, collected using vehicles. We also address the problem of utilizing that data in ego-motion estimation. There are seven factors that determine the magnitude of the uncertainty of a GNSS sensor. Because it is impossible to measure each of these factors, in this study, the uncertainty of the GNSS sensor is expressed through three variables, and the exact uncertainty is calculated. Using the proposed method, the uncertainty of the sensor is quantitatively modeled and robust localization is performed in a real environment. The approach is validated through experiments in urban environments.

scholarly journals Assessment of the Cutting Performance of a Robot Mower Using Custom Built Software

Agronomy ◽  
2019 ◽  
Vol 9 (5) ◽  
pp. 230 ◽  
Author(s):  
Luisa Martelloni ◽  
Marco Fontanelli ◽  
Stefano Pieri ◽  
Christian Frasconi ◽  
Lisa Caturegli ◽  
...  
Keyword(s):  
Autonomous Vehicles ◽  
Global Navigation Satellite Systems ◽  
Forward Speed ◽  
Satellite Systems ◽  
Different Shapes ◽  
Global Navigation Satellite ◽  
High Level ◽  
Short Time ◽  
Gnss Data ◽  
Collection And Management

Before the introduction of positioning technologies in agriculture practices such as global navigation satellite systems (GNSS), data collection and management were time-consuming and labor-intensive tasks. Today, due to the introduction of advanced technologies, precise information on the performance of agricultural machines, and smaller autonomous vehicles such as robot mowers, can be collected in a relatively short time. The aim of this work was to track the performance of a robot mower in various turfgrass areas of an equal number of square meters but with four different shapes by using real-time kinematic (RTK)-GNSS devices, and to easily extract data by a custom built software capable of calculating the distance travelled by the robot mower, the forward speed, the cutting area, and the number of intersections of the trajectories. These data were then analyzed in order to provide useful functioning information for manufacturers, entrepreneurs, and practitioners. The path planning of the robot mower was random and the turfgrass area for each of the four shapes was 135 m2 without obstacles. The distance travelled by the robot mower, the mean forward speed, and the intersections of the trajectories were affected by the interaction between the time of cutting and the shape of the turfgrass. For all the different shapes, the whole turfgrass area was completely cut after two hours of mowing. The cutting efficiency decreased by increasing the time, as a consequence of the increase in overlaps. After 75 minutes of cutting, the efficiency was about 35% in all the turfgrass areas shapes, thus indicating a high level of overlapping.

scholarly journals Context-Aware Sensor Uncertainty Estimation for Autonomous Vehicles

Vehicles ◽  
2021 ◽  
Vol 3 (4) ◽  
pp. 721-735
Author(s):  
Mohammed Alharbi ◽  
Hassan A. Karimi
Keyword(s):  
Autonomous Vehicles ◽  
Real Data ◽  
Global Navigation Satellite Systems ◽  
Learning Approach ◽  
Context Aware ◽  
Satellite Systems ◽  
Sensor Performance ◽  
Machine Learning Approach ◽  
Global Navigation Satellite ◽  
Data Acquisition Process

Sensor uncertainty significantly affects the performance of autonomous vehicles (AVs). Sensor uncertainty is predominantly linked to sensor specifications, and because sensor behaviors change dynamically, the machine learning approach is not suitable for learning them. This paper presents a novel learning approach for predicting sensor performance in challenging environments. The design of our approach incorporates both epistemic uncertainties, which are related to the lack of knowledge, and aleatoric uncertainties, which are related to the stochastic nature of the data acquisition process. The proposed approach combines a state-based model with a predictive model, where the former estimates the uncertainty in the current environment and the latter finds the correlations between the source of the uncertainty and its environmental characteristics. The proposed approach has been evaluated on real data to predict the uncertainties associated with global navigation satellite systems (GNSSs), showing that our approach can predict sensor uncertainty with high confidence.

Dynamic GNSS Mission Planning Using DTM for Precise Navigation of Autonomous Vehicles

2016 ◽  
Vol 70 (3) ◽  
pp. 483-504 ◽  
Author(s):  
Aleksander Nowak
Keyword(s):  
Autonomous Vehicles ◽  
Autonomous Vehicle ◽  
Digital Terrain Model ◽  
Dead Reckoning ◽  
Urban Environments ◽  
Mission Planning ◽  
Global Navigation Satellite Systems ◽  
Satellite Systems ◽  
Terrain Model ◽  
Global Navigation Satellite

Nowadays, the most widely used method for estimating location of autonomous vehicles in real time is the use of Global Navigation Satellite Systems (GNSS). However, positioning in urban environments using GNSS is hampered by poor satellite geometry due to signal obstruction created by both man-made and natural features of the urban environment. The presence of obstacles is the reason for the decreased number of observed satellites as well as uncertainty of GNSS positioning. It is possible that in some sections of the vehicle route there might not be enough satellites necessary to fix position. It is common to use software for static GNSS measurement campaign planning, but it is often only able to predict satellite visibility at one point. This article presents a proposal for dynamic GNSS mission planning using a Digital Terrain Model (DTM) and dead reckoning. The methodology and sample results of numerical experiments are also described. They clearly show that proper dynamic GNSS mission planning is necessary in order to complete a task by an autonomous vehicle in an obstructed environment.

scholarly journals Application of Robust Estimation Method for Establishing 3D Combined Terrestrial and GNSS Network: A case of a Quarry in Lang Son, Vietnam

2020 ◽  
Vol 1 (2) ◽  
Author(s):  
Luu ANH TUAN ◽  
Hoang NGOC HA ◽  
La PHU HIEN ◽  
Pham VAN CHUNG
Keyword(s):  
Data Processing ◽  
Robust Estimation ◽  
Weighting Function ◽  
Estimation Method ◽  
Geodetic Network ◽  
Global Navigation Satellite Systems ◽  
Satellite Systems ◽  
Gnss Network ◽  
Global Navigation Satellite ◽  
Mine Surveying

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.

scholarly journals A Survey of Localization Methods for Autonomous Vehicles in Highway Scenarios

Sensors ◽  
2021 ◽  
Vol 22 (1) ◽  
pp. 247
Author(s):  
Johann Laconte ◽  
Abderrahim Kasmi ◽  
Romuald Aufrère ◽  
Maxime Vaidis ◽  
Roland Chapuis
Keyword(s):  
Autonomous Vehicles ◽  
Global Navigation Satellite Systems ◽  
Safe Driving ◽  
Satellite Systems ◽  
The Road ◽  
Current Localization ◽  
On The Road ◽  
Main Components ◽  
Main Component ◽  
Global Navigation Satellite

In the context of autonomous vehicles on highways, one of the first and most important tasks is to localize the vehicle on the road. For this purpose, the vehicle needs to be able to take into account the information from several sensors and fuse them with data coming from road maps. The localization problem on highways can be distilled into three main components. The first one consists of inferring on which road the vehicle is currently traveling. Indeed, Global Navigation Satellite Systems are not precise enough to deduce this information by themselves, and thus a filtering step is needed. The second component consists of estimating the vehicle’s position in its lane. Finally, the third and last one aims at assessing on which lane the vehicle is currently driving. These two last components are mandatory for safe driving as actions such as overtaking a vehicle require precise information about the current localization of the vehicle. In this survey, we introduce a taxonomy of the localization methods for autonomous vehicles in highway scenarios. We present each main component of the localization process, and discuss the advantages and drawbacks of the associated state-of-the-art methods.

Global reliance on GPS creates new risks

2019 ◽  
Keyword(s):  
Power Distribution ◽  
Autonomous Vehicles ◽  
Critical Infrastructure ◽  
Organised Crime ◽  
Global Navigation Satellite Systems ◽  
Economic Losses ◽  
Navigation Systems ◽  
Content Type ◽  
Satellite Systems ◽  
Global Navigation Satellite

Subject Reliance on GPS. Significance Critical infrastructure, essential services and entire industries have become dependent on global navigation satellite systems (GNSSs). This dependence has emerged in an unplanned and unanticipated manner. GNSSs are vulnerable to disruption, with a risk of serious economic losses, loss of life and threats to national security. Impacts Reliance on GNSS will rise in established industries, notably finance, power distribution, agriculture and transportation. GNSS will be vital to the successful development of emerging industries such as autonomous vehicles, drones and new space systems. Demand will grow for high-quality GNSS receivers and software, and for backup systems such as ground-based radio navigation systems. Rising dependence on GNSS will incentivise efforts by national militaries and organised crime to exploit vulnerabilities. The greatest vulnerabilities may emerge in poorer countries where finances are more constrained and regulation is likely to be weaker.

scholarly journals GLOBAL NAVIGATION SATELLITE SYSTEMS AND THEIR ROLE IN PRECISION AGRICULTURE TECHNOLOGIES

2020 ◽  
pp. 71-87
Author(s):  
Oleksandr Kholodyuk
Keyword(s):  
Precision Agriculture ◽  
Satellite Navigation ◽  
Global Navigation Satellite Systems ◽  
Navigation Satellite ◽  
Navigation Systems ◽  
Satellite Systems ◽  
Global Positioning ◽  
Global Navigation ◽  
Satellite Navigation Systems ◽  
Global Navigation Satellite

Today, global navigation satellite systems are being implemented in many structural units of the Ukrainian economic complex, many spheres of human activity, and every year they continue to develop. One of the main feature of these satellite systems is the requirements for high accuracy and speed of received data. They provide the opportunity to reduce operating costs and increase the efficiency of use of equipment and other resources. Therefore, the use of navigation satellite systems for controlling machine units, establishing their location, monitoring soil condition and yield mapping is becoming increasingly relevant today. The subject of study in this article were global navigation satellite systems NAVSTARGPS (USA), GLONASS (RF), GALILEO (EU), BEIDOU (China) and regional navigation systems NavIC (India) and QUASI-ZENITH (Japan). The purpose of the work was to clarify and establish the main characteristics of global navigation satellite systems and their role in the implementation of precision agriculture technologies. The task of the work was: to analyze the functional characteristics of global positioning satellite systems and their main elements; to find out principles of operation of systems: navigation, coordinates, time; to establish the accuracy of navigation systems; to substantiate the role of global positioning satellite systems in the effective implementation of precision agriculture technologies in agriculture. The research methodology was based on the method of materialistic dialectics, methods of analysis and synthesis of both information from official sources and information from the works of other researchers. Two major operators of satellite navigation systems the NAVSTAR GPS and GLONASS, which are similar in many respects, have been identified in the scientific work. Among the distinctive features there are the nature of the location, the motion of satellites in orbits and their total number, methods of encoding the CDMA and FDMA signals, the use of different coordinate systems WGS-84 and PZ90.11. As for the other two satellite navigation systems GALILEO and BEIDOU, they are developing rapidly with great ambition and potential. It is established that at the present time the accuracy of determining the coordinates of the GLONASS system is inferior to the performance of the American satellite navigation system GPS. GLONASS provides more accurate positioning in the northern latitudes and GPS in the middle. It is noted that the positioning accuracy of machine units for the implementation of precision farming technologies can be improved (from 2 to 20 cm) due to differential signal correction with the help of free and commercial wideband satellite navigation subsystems. These services will allow to implement the tasks of precision driving, and therefore, to ensure the accurate implementation of sowing material, fertilizers and herbicides to spare them, accurate inter-row cultivation of industrial crops, accurate harvesting, etc., when performing agro-technological operations using ground vehicles and landless vehicles.

scholarly journals COMPARATIVE EVALUATION OF DERIVED IMAGE AND LIDAR POINT CLOUDS FROM UAV-BASED MOBILE MAPPING SYSTEMS

2020 ◽  
Vol XLIII-B2-2020 ◽  
pp. 169-175
Author(s):  
T. Zhou ◽  
S. M. Hasheminasab ◽  
Y.-C. Lin ◽  
A. Habib
Keyword(s):  
Precision Agriculture ◽  
Point Clouds ◽  
Global Navigation Satellite Systems ◽  
Navigation Systems ◽  
Mobile Mapping ◽  
Satellite Systems ◽  
Area Of Interest ◽  
Effective Option ◽  
Mobile Mapping System ◽  
Global Navigation Satellite

Abstract. Unmanned aerial vehicles (UAVs) have been widely used for 3D reconstruction/modelling in various applications such as precision agriculture, coastal monitoring, and emergency management. For such mapping applications, camera and LiDAR are the two most commonly used sensors. Mapping with imagery-based approaches is considered to be an economical and effective option and is often conducted using Structure from Motion (SfM) techniques where point clouds and orthophotos are generated. In addition to UAV photogrammetry, point clouds of the area of interest can also be directly derived from LiDAR sensors onboard UAVs equipped with global navigation satellite systems/inertial navigation systems (GNSS/INS). In this study, a custom-built UAV-based mobile mapping system is used to simultaneously collect imagery and LiDAR data. Derived LiDAR and image-based point clouds are investigated and compared in terms of their absolute and relative accuracy. Furthermore, stability of the system calibration parameters for the camera and LiDAR sensors are studied using temporal datasets. The results show that while LiDAR point clouds demonstrate a high absolute accuracy over time, image-based point clouds are not as accurate as LiDAR due to instability of the camera interior orientation parameters.

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