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.

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 Kalman Filter-Based RAIM for Reliable Aircraft Positioning with GPS and NavIC Constellations

Sensors ◽  
2020 ◽  
Vol 20 (22) ◽  
pp. 6606
Author(s):  
Susmita Bhattacharyya ◽  
Dinesh Mute
Keyword(s):  
Kalman Filter ◽  
Weighted Least Squares ◽  
Unmanned Aircraft ◽  
Global Navigation Satellite Systems ◽  
Navigation Systems ◽  
Satellite Systems ◽  
Vector Tracking ◽  
Receiver Autonomous Integrity Monitoring ◽  
Global Navigation Satellite ◽  
Computational Resources

This paper presents a novel Kalman filter (KF)-based receiver autonomous integrity monitoring (RAIM) algorithm for reliable aircraft positioning with global navigation satellite systems (GNSS). The presented method overcomes major limitations of the authors’ previous work, and uses two GNSS, namely, Navigation with Indian Constellation (NavIC) of India and the Global Positioning System (GPS). The algorithm is developed in the range domain and compared with two existing approaches—one each for the weighted least squares navigation filter and KF. Extensive simulations were carried out for an unmanned aircraft flight path over the Indian sub-continent for validation of the new approach. Although both existing methods outperform the new one, the work is significant for the following reasons. KF is an integral part of advanced navigation systems that can address frequent loss of GNSS signals (e.g., vector tracking and multi-sensor integration). Developing KF RAIM algorithms is essential to ensuring their reliability. KF solution separation (or position domain) RAIM offers good performance at the cost of high computational load. Presented range domain KF RAIM, on the other hand, offers satisfactory performance to a certain extent, eliminating a major issue of growing position error bounds over time. It requires moderate computational resources, and hence, shows promise for real-time implementations in avionics. Simulation results also indicate that addition of NavIC alongside GPS can substantially improve RAIM performance, particularly in poor geometries.

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 %.

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 Integrity Analysis for GPS-Based Navigation of UAVs in Urban Environment

Robotics ◽  
2020 ◽  
Vol 9 (3) ◽  
pp. 66
Author(s):  
Oguz Kagan Isik ◽  
Juhyeon Hong ◽  
Ivan Petrunin ◽  
Antonios Tsourdos
Keyword(s):  
Urban Environment ◽  
Urban Areas ◽  
Environmental Parameters ◽  
Urban Environments ◽  
Rate Of Change ◽  
Global Navigation Satellite Systems ◽  
Integrity Monitoring ◽  
Satellite Systems ◽  
Joint Consideration ◽  
Global Navigation Satellite

The increasing use of Unmanned Aerial Vehicles (UAVs) in safety-critical missions in both civilian and military areas demands accurate and reliable navigation, where one of the key sources of navigation information is presented by Global Navigation Satellite Systems (GNSS). In challenging conditions, for example, in urban areas, the accuracy of GNSS-based navigation may degrade significantly due to user-satellite geometry and obscuration issues without being noticed by the user. Therefore, considering the essentially dynamic rate of change in this type of environment, integrity monitoring is of critical importance for understanding the level of trust we have in positioning and timing data. In this paper, the dilution of precision (DOP) coefficients under nominal and challenging conditions were investigated for the purpose of integrity monitoring in urban environments. By analyzing positioning information in a simulated urban environment using a software-based GNSS receiver, the integrity monitoring approach based on joint consideration of GNSS observables and environmental parameters has been proposed. It was shown that DOP coefficients, when considered together with a number of visible satellites and cut-off elevations specific to the urban environment carry valuable integrity information that is difficult to get using existing integrity monitoring approaches. This has allowed generating indirect integrity measures based on cut-off elevation and satellite visibility that can be used for UAV path planning and guidance in urban environments.

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.

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