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 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.

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 Seamless Vehicle Positioning by Lidar-GNSS Integration: Standalone and Multi-Epoch Scenarios

2021 ◽  
Vol 13 (22) ◽  
pp. 4525
Author(s):  
Junjie Zhang ◽  
Kourosh Khoshelham ◽  
Amir Khodabandeh
Keyword(s):  
Autonomous Driving ◽  
Measurement Model ◽  
Urban Environments ◽  
Global Navigation Satellite Systems ◽  
High Definition ◽  
Satellite Systems ◽  
The Road ◽  
Gnss Receivers ◽  
Vehicle Positioning ◽  
Global Navigation Satellite

Accurate and seamless vehicle positioning is fundamental for autonomous driving tasks in urban environments, requiring the provision of high-end measuring devices. Light Detection and Ranging (lidar) sensors, together with Global Navigation Satellite Systems (GNSS) receivers, are therefore commonly found onboard modern vehicles. In this paper, we propose an integration of lidar and GNSS code measurements at the observation level via a mixed measurement model. An Extended Kalman-Filter (EKF) is implemented to capture the dynamic of the vehicle movement, and thus, to incorporate the vehicle velocity parameters into the measurement model. The lidar positioning component is realized using point cloud registration through a deep neural network, which is aided by a high definition (HD) map comprising accurately georeferenced scans of the road environments. Experiments conducted in a densely built-up environment show that, by exploiting the abundant measurements of GNSS and high accuracy of lidar, the proposed vehicle positioning approach can maintain centimeter-to meter-level accuracy for the entirety of the driving duration in urban canyons.

scholarly journals GNSS Performance Modelling and Augmentation for Urban Air Mobility

Sensors ◽  
2019 ◽  
Vol 19 (19) ◽  
pp. 4209 ◽  
Author(s):  
Suraj Bijjahalli ◽  
Roberto Sabatini ◽  
Alessandro Gardi
Keyword(s):  
Failure Modes ◽  
Primary Source ◽  
Urban Environments ◽  
Unmanned Aircraft ◽  
Global Navigation Satellite Systems ◽  
Urban Air ◽  
Performance Modelling ◽  
Satellite Systems ◽  
Urban Structures ◽  
Global Navigation Satellite

One of the primary challenges facing Urban Air Mobility (UAM) and the safe integration of Unmanned Aircraft Systems (UAS) in the urban airspace is the availability of robust, reliable navigation and Sense-and-Avoid (SAA) systems. Global Navigation Satellite Systems (GNSS) are typically the primary source of positioning for most air and ground vehicles and for a growing number of UAS applications; however, their performance is frequently inadequate in such challenging environments. This paper performs a comprehensive analysis of GNSS performance for UAS operations with a focus on failure modes in urban environments. Based on the analysis, a guidance strategy is developed which accounts for the influence of urban structures on GNSS performance. A simulation case study representative of UAS operations in urban environments is conducted to assess the validity of the proposed approach. Results show improved accuracy (approximately 25%) and availability when compared against a conventional minimum-distance guidance strategy.

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 QUALITY OF SATELLITE COMMUNICATION IN SELECTED MOBILE ANDROID SMARTPHONES

2021 ◽  
Vol 11 (4) ◽  
pp. 32-37
Author(s):  
Przemysław Falkowski-Gilski
Keyword(s):  
Mobile Devices ◽  
Satellite Communication ◽  
Urban Environments ◽  
Global Navigation Satellite Systems ◽  
Mobile Terminals ◽  
Everyday Activity ◽  
Satellite Systems ◽  
Global Navigation Satellite ◽  
Application Developers

Today, thanks to mobile devices, satellite communication is available to anyone and everywhere. Gaining information on one’s position using GNSS (Global Navigation Satellite Systems), particularly in unknown urban environments, had become an everyday activity. With the widespread of mobile devices, particularly smartphones, each person can obtain information considering his or her location anytime and everywhere. This paper is focused on a study, considering the quality of satellite communication in case of selected mobile terminals. It describes a measurement campaign carried out in varying urban environments, including a set of Android-powered smartphones coming from different manufacturers. Based on this, respective conclusions and remarks are given, which can aid consumers as well as device manufacturers and application developers.

scholarly journals FULLY AUTOMATIC FEATURE-BASED REGISTRATION OF MOBILE MAPPING AND AERIAL NADIR IMAGES FOR ENABLING THE ADJUSTMENT OF MOBILE PLATFORM LOCATIONS IN GNSS-DENIED URBAN ENVIRONMENTS

2017 ◽  
Vol XLII-1/W1 ◽  
pp. 317-323 ◽  
Author(s):  
P. Jende ◽  
F. Nex ◽  
M. Gerke ◽  
G. Vosselman
Keyword(s):  
Urban Areas ◽  
Urban Environments ◽  
Global Navigation Satellite Systems ◽  
Aerial Images ◽  
Mobile Mapping ◽  
High Resolution Data ◽  
Satellite Systems ◽  
Correct Orientation ◽  
Fully Automatic ◽  
Global Navigation Satellite

Mobile Mapping (MM) has gained significant importance in the realm of high-resolution data acquisition techniques. MM is able to record georeferenced street-level data in a continuous (laser scanners) and/or discrete (cameras) fashion. MM’s georeferencing relies on a conjunction of Global Navigation Satellite Systems (GNSS), Inertial Measurement Units (IMU) and optionally on odometry sensors. While this technique does not pose a problem for absolute positioning in open areas, its reliability and accuracy may be diminished in urban areas where high-rise buildings and other tall objects can obstruct the direct line-of-sight between the satellite and the receiver unit. Consequently, multipath measurements or complete signal outages impede the MM platform’s localisation and may affect the accurate georeferencing of collected data. This paper presents a technique to recover correct orientation parameters for MM imaging platforms by utilising aerial images as an external georeferencing source. This is achieved by a fully automatic registration strategy which takes into account the overall differences between aerial and MM data, such as scale, illumination, perspective and content. Based on these correspondences, MM data can be verified and/or corrected by using an adjustment solution. The registration strategy is discussed and results in a success rate of about 95 %.

scholarly journals TRANSLATING AERIAL IMAGES INTO STREET-MAP-LIKE REPRESENTATIONS FOR VISUAL SELF-LOCALIZATION OF UAVS

2019 ◽  
Vol XLII-2/W13 ◽  
pp. 575-580 ◽  
Author(s):  
M. Schleiss
Keyword(s):  
Global Positioning System ◽  
Global Navigation Satellite Systems ◽  
Aerial Imagery ◽  
Aerial Images ◽  
Visual Localization ◽  
Localization Accuracy ◽  
Satellite Systems ◽  
Global Positioning ◽  
Reference Map ◽  
Global Navigation Satellite

<p><strong>Abstract.</strong> Unmanned aerial vehicles (UAVs) rely on global navigation satellite systems (GNSS) like the Global Positioning System (GPS) for navigation but GNSS signals can be easily jammed. Therefore, we propose a visual localization method that uses a camera and data from Open Street Maps in order to replace GNSS. First, the aerial imagery from the onboard camera is translated into a map-like representation. Then we match it with a reference map to infer the vehicle’s position. An experiment over a typical sized mission area shows localization accuracy close to commercial GPS. Compared to previous methods ours is applicable to a broader range of scenarios. It can incorporate multiple types of landmarks like roads and buildings and it outputs absolute positions with higher frequency and confidence and can be used at altitudes typical for commercial UAVs. Our results show that the proposed method can serve as a backup to GNSS systems where suitable landmarks are available.</p>

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