scholarly journals A High-Accuracy GNSS Dataset of Ground Truth Points Collected within Îles-de-Boucherville National Park, Quebec, Canada

Data ◽  
2021 ◽  
Vol 6 (3) ◽  
pp. 32
Author(s):  
Kathryn Elmer ◽  
Margaret Kalacska
Keyword(s):  
National Park ◽  
Hyperspectral Imagery ◽  
Ground Truth ◽  
High Accuracy ◽  
Global Navigation Satellite Systems ◽  
Validation Data ◽  
Ground Truth Data ◽  
Satellite Systems ◽  
Study Sites ◽  
Global Navigation Satellite

A new ground truth dataset generated with high-accuracy Global Navigation Satellite Systems (GNSS) positional data of the invasive reed Phragmites australis subsp. australis within Îles-de-Boucherville National Park (Quebec, Canada) is described. The park is one of five study sites for the Canadian Airborne Biodiversity Observatory (CABO) and has stands of invasive P. australis spread throughout the park. Previously, within the context of CABO, no ground truth data had been collected within the park consolidating the locations of P. australis. This dataset was collected to serve as training and validation data for CABO airborne hyperspectral imagery acquired in 2019 to assist with the detection and mapping of P. australis. The locations of the ground truth points were found to be accurate within one pixel of the hyperspectral imagery. Overall, 320 ground truth points were collected, representing 158 locations where P. australis was present and 162 locations where it was absent. Auxiliary data includes field photographs and digitized field notes that provide context for each point.

An Innovative Approach for Atmospheric Error Mitigation Using New GNSS Signals

2011 ◽  
Vol 64 (S1) ◽  
pp. S211-S232 ◽  
Author(s):  
Lei Yang ◽  
Zeynep Elmas ◽  
Chris Hill ◽  
Marcio Aquino ◽  
Terry Moore
Keyword(s):  
High Accuracy ◽  
Global Navigation Satellite Systems ◽  
Tropospheric Delay ◽  
Atmospheric Effects ◽  
Navigation Satellite ◽  
Navigation Systems ◽  
Satellite Systems ◽  
Error Mitigation ◽  
Satellite Navigation Systems ◽  
Global Navigation Satellite

New signals from the modernised satellite navigation systems (GPS and GLONASS) and the ones that are being developed (COMPASS and GALILEO) will present opportunities for more accurate and reliable positioning solutions. Successful exploitation of these new signals will also enable the development of new markets and applications for difficult environments where the current Global Navigation Satellite Systems (GNSS) cannot provide satisfying solutions. This research is aiming to exploit the improvement in monitoring, modelling and mitigating the atmospheric effects using the increased number of signals from the future satellite systems. Preliminary investigations were conducted on the numerical weather parameter based horizontal tropospheric delay modelling, as well as the ionospheric higher order and scintillation effects. Results from this research are expected to provide a potential supplement to high accuracy positioning techniques.

scholarly journals A New Algorithm for Lane Level Irregular Driving Identification

2015 ◽  
Vol 68 (6) ◽  
pp. 1173-1194 ◽  
Author(s):  
Rui Sun ◽  
Washington Ochieng ◽  
Cheng Fang ◽  
Shaojun Feng
Keyword(s):  
Intelligent Transportation System ◽  
Fuzzy Inference ◽  
High Accuracy ◽  
Global Navigation Satellite Systems ◽  
Inference System ◽  
Satellite Systems ◽  
Motion Models ◽  
Driving Behaviour ◽  
Different Types ◽  
Global Navigation Satellite

Global Navigation Satellite Systems (GNSS) are used widely in the provision of Intelligent Transportation System (ITS) services. Today, there is an increasing demand on GNSS to support applications at lane level. These applications required at lane level include lane control, collision avoidance and intelligent speed assistance. In lane control, detecting irregular driving behaviour within the lane is a basic requirement for safety related lane level applications. There are two major issues involved in lane level irregular driving identification: access to high accuracy positioning and vehicle dynamic parameters, and extraction of erratic driving behaviour from this and other related information. This paper proposes an integrated algorithm for lane level irregular driving identification. Access to high accuracy positioning is enabled by GNSS and its integration with an Inertial Navigation System (INS) using filtering with precise vehicle motion models and lane information. The identification of irregular driving behaviour is achieved by algorithms developed for different types of events based on the application of a Fuzzy Inference System (FIS). The results show that decimetre level accuracy can be achieved and that different types of lane level irregular driving behaviour can be identified.

scholarly journals Motorway Measurement Campaign to Support R&D Activities in the Field of Automated Driving Technologies

Sensors ◽  
2021 ◽  
Vol 21 (6) ◽  
pp. 2169
Author(s):  
Viktor Tihanyi ◽  
Tamás Tettamanti ◽  
Mihály Csonthó ◽  
Arno Eichberger ◽  
Dániel Ficzere ◽  
...  
Keyword(s):  
Ground Truth ◽  
Global Navigation Satellite Systems ◽  
Sensor Data ◽  
Automated Driving ◽  
High Definition ◽  
Data Set ◽  
Measurement Campaign ◽  
Satellite Systems ◽  
Road Geometry ◽  
Global Navigation Satellite

A spectacular measurement campaign was carried out on a real-world motorway stretch of Hungary with the participation of international industrial and academic partners. The measurement resulted in vehicle based and infrastructure based sensor data that will be extremely useful for future automotive R&D activities due to the available ground truth for static and dynamic content. The aim of the measurement campaign was twofold. On the one hand, road geometry was mapped with high precision in order to build Ultra High Definition (UHD) map of the test road. On the other hand, the vehicles—equipped with differential Global Navigation Satellite Systems (GNSS) for ground truth localization—carried out special test scenarios while collecting detailed data using different sensors. All of the test runs were recorded by both vehicles and infrastructure. The paper also showcases application examples to demonstrate the viability of the collected data having access to the ground truth labeling. This data set may support a large variety of solutions, for the test and validation of different kinds of approaches and techniques. As a complementary task, the available 5G network was monitored and tested under different radio conditions to investigate the latency results for different measurement scenarios. A part of the measured data has been shared openly, such that interested automotive and academic parties may use it for their own purposes.

scholarly journals GPS/Galileo Multipath Detection and Mitigation Using Closed-Form Solutions

2009 ◽  
Vol 2009 ◽  
pp. 1-20 ◽  
Author(s):  
Khaled Rouabah ◽  
Djamel Chikouche
Keyword(s):  
High Performance ◽  
High Accuracy ◽  
Global Navigation Satellite Systems ◽  
Line Of Sight ◽  
Satellite Systems ◽  
Closed Form Solutions ◽  
Gnss Positioning ◽  
Simulation Results ◽  
Multipath Detection ◽  
Global Navigation Satellite

We propose an efficient method for the detection of Line of Sight (LOS) and Multipath (MP) signals in global navigation satellite systems (GNSSs) which is based on the use of virtual MP mitigation (VMM) technique. By using the proposed method, the MP signals' delay and coefficient amplitudes can be efficiently estimated. According to the computer simulation results, it is obvious that our proposed method is a solution for obtaining high performance in the estimation and mitigation of MP signals and thus it results in a high accuracy in GNSS positioning.

An Evaluation of the Increase in the Quality and Quantity of Navigational Information Available from Low-Frequency Radio Navigation Systems

1999 ◽  
Vol 52 (3) ◽  
pp. 411-417
Author(s):  
Victor Filin
Keyword(s):  
Coastal Waters ◽  
Low Cost ◽  
Low Frequency ◽  
High Accuracy ◽  
Global Navigation Satellite Systems ◽  
Navigation Satellite ◽  
Navigation Systems ◽  
Satellite Systems ◽  
Radio Navigation ◽  
Global Navigation Satellite

Low frequency radio navigation systems continue to play an important role in the provision of precise navigation for vessels sailing in coastal waters, and in other zones requiring high accuracy. Modernization of the existing Loran C chains, and deployment of new ones, shows there is strong interest in these systems despite the appearance of global navigation satellite systems (GNSS) such as ‘Navstar’ and ‘Glonass’. This continuation of interest is connected to the relatively low cost of operation of the systems, the low cost of receiver-indicators and the need to provide users with very precise but reliable positioning information, which at present can only be obtained by joint use of GNSS and Loran C. To make the most of such an approach, Loran C should provide accuracy and reliability similar to GNSS.

GNSS Positioning Enhancement Based on NLOS Multipath Biases Estimation Using Gaussian Mixture Noise

2021 ◽  
pp. 632-652
Author(s):  
Guermah Bassma ◽  
Sadiki Tayeb ◽  
El Ghazi Hassan
Keyword(s):  
Em Algorithm ◽  
Statistical Tests ◽  
Hybrid Approach ◽  
Gaussian Mixture ◽  
High Accuracy ◽  
Global Navigation Satellite Systems ◽  
Positioning System ◽  
Satellite Systems ◽  
Global Positioning ◽  
Global Navigation Satellite

Global navigation satellite systems (GNSS) have been widely used in many applications where positioning plays an important role. However, the performances of these applications can be degraded in urban canyons, due to Non-Line-Of-Sight (NLOS) and Multipath interference affecting GNSS signals. In order to ensure high accuracy positioning, this article proposes to model the NLOS and Multipath biases by Gaussian Mixture noise using Expectation Maximization (EM) algorithm. In this context, an approach to estimate the Multipath and NLOS biases for real time positioning is presented and statistical tests for searching the probability distribution of NLOS and Multipath biases are illustrated. Furthermore, a hybrid approach based on PF (Particle Filter) and EM algorithm for estimating user position in hard environment is presented. Using real GPS (Global Positioning System) signal, the efficiency of the proposed approach is shown, and a significant improvement of the positioning accuracy over the simple PF estimation is obtained.

scholarly journals Sensitivity of TDS-1 GNSS-R Reflectivity to Soil Moisture: Global and Regional Differences and Impact of Different Spatial Scales

2018 ◽  
Vol 10 (11) ◽  
pp. 1856 ◽  
Author(s):  
Adriano Camps ◽  
Mercedes Vall·llossera ◽  
Hyuk Park ◽  
Gerard Portal ◽  
Luciana Rossato
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Incidence Angle ◽  
Spatial Scales ◽  
Ground Truth ◽  
Global Navigation Satellite Systems ◽  
Satellite Systems ◽  
Left Hand ◽  
The Uk ◽  
Global Navigation Satellite

The potential of Global Navigation Satellite Systems-Reflectometry (GNSS-R) techniques to estimate land surface parameters such as soil moisture (SM) is experimentally studied using 2014–2017 global data from the UK TechDemoSat-1 (TDS-1) mission. The approach is based on the analysis of the sensitivity to SM of different observables extracted from the Delay Doppler Maps (DDM) computed by the Space GNSS Receiver–Remote Sensing Instrument (SGR-ReSI) instrument using the L1 (1575.42 MHz) left-hand circularly-polarized (LHCP) reflected signals emitted by the Global Positioning System (GPS) navigation satellites. The sensitivity of different GNSS-R observables to SM and its dependence on the incidence angle is analyzed. It is found that the sensitivity of the calibrated GNSS-R reflectivity to surface soil moisture is ~0.09 dB/% up to 30° incidence angle, and it decreases with increasing incidence angles, although differences are found depending on the spatial scale used for the ground-truth, and the region. The sensitivity to subsurface soil moisture has been also analyzed using a network of subsurface probes and hydrological models, apparently showing some dependence, but so far results are not conclusive.

scholarly journals Methodology for Simulating 5G and GNSS High-Accuracy Positioning

Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3220 ◽  
Author(s):  
José del Peral-Rosado ◽  
Jani Saloranta ◽  
Giuseppe Destino ◽  
José López-Salcedo ◽  
Gonzalo Seco-Granados
Keyword(s):  
High Accuracy ◽  
Urban Environments ◽  
Global Navigation Satellite Systems ◽  
Base Stations ◽  
Line Of Sight ◽  
Millimetre Wave ◽  
Localization Accuracy ◽  
Satellite Systems ◽  
Hybrid Positioning ◽  
Global Navigation Satellite

This paper focuses on the exploitation of fifth generation (5G) centimetre-wave (cmWave) and millimetre-wave (mmWave) transmissions for high-accuracy positioning, in order to complement the availability of Global Navigation Satellite Systems (GNSS) in harsh environments, such as urban canyons. Our goal is to present a representative methodology to simulate and assess their hybrid positioning capabilities over outdoor urban, suburban and rural scenarios. A novel scenario definition is proposed to integrate the network density of 5G deployments with the visibility masks of GNSS satellites, which helps to generate correlated scenarios of both technologies. Then, a generic and representative modeling of the 5G and GNSS observables is presented for snapshot positioning, which is suitable for standard protocols. The simulations results indicate that GNSS drives the achievable accuracy of its hybridisation with 5G cmWave, because non-line-of-sight (NLoS) conditions can limit the cmWave localization accuracy to around 20 m. The 5G performance is significantly improved with the use of mmWave positioning with dominant line-of-sight (LoS) conditions, which can even achieve sub-meter localization with one or more base stations. Therefore, these results show that NLoS conditions need to be weighted in 5G localization, in order to complement and outperform GNSS positioning over urban environments.

scholarly journals Comparison of Different Hardware Configurations for 2D SLAM Techniques Based on Google Cartographer Use Case

2021 ◽  
Author(s):  
Łukasz Sobczak ◽  
Katarzyna Filus ◽  
Joanna Domańska ◽  
Adam Domański
Keyword(s):  
Real Life ◽  
Ground Truth ◽  
Cost Effective ◽  
Global Navigation Satellite Systems ◽  
Use Case ◽  
Indoor Environments ◽  
Satellite Systems ◽  
Localization And Mapping ◽  
Hardware Configuration ◽  
Global Navigation Satellite

Abstract One of the most challenging topics in Robotics is Simultaneous Localization and Mapping (SLAM) in the indoor environments. Due to the fact that Global Navigation Satellite Systems cannot be successfully used in such environments, different data sources are used for this purpose, among others LiDARs (Light Detection and Ranging), which have advanced from numerous other technologies. Other embedded sensors can be used along with LiDARs to improve SLAM accuracy, e.g. the ones available in the Inertial Measurement Units and wheel odometry sensors. Evaluation of different SLAM algorithms and possible hardware configurations in real environments is time consuming and expensive. For that reason, in this paper we evaluate the performance of different hardware configuration used with Google Cartographer SLAM algorithms in simulation framework proposed in 1. Our use case is an actual robot used for room decontamination. The results show that for our robot the best hardware configuration consists of three LiDARs 2D, IMU and wheel odometry sensors. The proposed simulation-based methodology is a cost-effective alternative to real-world evaluation. It allows easy automation and provides access to precise ground truth. It is especially beneficial in the early stages of product design and to reduce the number of necessary real-life tests and hardware configurations.

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