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 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 Filtering Link Outliers in Vehicle Trajectories by Spatial Reasoning

2021 ◽  
Vol 10 (5) ◽  
pp. 333
Author(s):  
Junli Liu ◽  
Miaomiao Pan ◽  
Xianfeng Song ◽  
Jing Wang ◽  
Kemin Zhu ◽  
...  
Keyword(s):  
Urban Areas ◽  
Spatial Reasoning ◽  
Sampling Interval ◽  
Global Navigation Satellite Systems ◽  
Quality Analysis ◽  
Ancillary Data ◽  
Satellite Systems ◽  
Positioning Errors ◽  
Vehicle Trajectories ◽  
Global Navigation Satellite

Vehicle trajectories derived from Global Navigation Satellite Systems (GNSS) are used in various traffic applications based on trajectory quality analysis for the development of successful traffic models. A trajectory consists of points and links that are connected, where both the points and links are subject to positioning errors in the GNSS. Existing trajectory filters focus on point outliers, but neglect link outliers on tracks caused by a long sampling interval. In this study, four categories of link outliers are defined, i.e., radial, drift, clustered, and shortcut; current available algorithms are applied to filter apparent point outliers for the first three categories, and a novel filtering approach is proposed for link outliers of the fourth category in urban areas using spatial reasoning rules without ancillary data. The proposed approach first measures specific geometric properties of links from trajectory databases and then evaluates the similarities of geometric measures among the links, following a set of spatial reasoning rules to determine link outliers. We tested this approach using taxi trajectory datasets for Beijing with a built-in sampling interval of 50 to 65 s. The results show that clustered links (27.14%) account for the majority of link outliers, followed by shortcut (6.53%), radial (3.91%), and drift (0.62%) outliers.

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.

scholarly journals Integrity and Collaboration in Dynamic Sensor Networks

Sensors ◽  
2018 ◽  
Vol 18 (7) ◽  
pp. 2400 ◽  
Author(s):  
Steffen Schön ◽  
Claus Brenner ◽  
Hamza Alkhatib ◽  
Max Coenen ◽  
Hani Dbouk ◽  
...  
Keyword(s):  
Sensor Networks ◽  
Urban Areas ◽  
Research Training ◽  
Training Group ◽  
Autonomous Driving ◽  
Global Navigation Satellite Systems ◽  
Satellite Systems ◽  
Global Navigation Satellite ◽  
Map Data ◽  
Dynamic Sensor Networks

Global Navigation Satellite Systems (GNSS) deliver absolute position and velocity, as well as time information (P, V, T). However, in urban areas, the GNSS navigation performance is restricted due to signal obstructions and multipath. This is especially true for applications dealing with highly automatic or even autonomous driving. Subsequently, multi-sensor platforms including laser scanners and cameras, as well as map data are used to enhance the navigation performance, namely in accuracy, integrity, continuity and availability. Although well-established procedures for integrity monitoring exist for aircraft navigation, for sensors and fusion algorithms used in automotive navigation, these concepts are still lacking. The research training group i.c.sens, integrity and collaboration in dynamic sensor networks, aims to fill this gap and to contribute to relevant topics. This includes the definition of alternative integrity concepts for space and time based on set theory and interval mathematics, establishing new types of maps that report on the trustworthiness of the represented information, as well as taking advantage of collaboration by improved filters incorporating person and object tracking. In this paper, we describe our approach and summarize the preliminary results.

scholarly journals Performance Analyses of a RAIM Algorithm for Kalman Filter with GPS and NavIC Constellations

Sensors ◽  
2021 ◽  
Vol 21 (24) ◽  
pp. 8441
Author(s):  
Susmita Bhattacharyya
Keyword(s):  
Kalman Filter ◽  
Measurement Errors ◽  
Weighted Least Squares ◽  
Temporal Variations ◽  
Global Navigation Satellite Systems ◽  
Model Parameters ◽  
Integrity Monitoring ◽  
Satellite Systems ◽  
Performance Analyses ◽  
Global Navigation Satellite

This paper evaluates the performance of an integrity monitoring algorithm of global navigation satellite systems (GNSS) for the Kalman filter (KF), termed KF receiver autonomous integrity monitoring (RAIM). The algorithm checks measurement inconsistencies in the range domain and requires Schmidt KF (SKF) as the navigation processor. First, realistic carrier-smoothed pseudorange measurement error models of GNSS are integrated into KF RAIM, overcoming an important limitation of prior work. More precisely, the error covariance matrix for fault detection is modified to capture the temporal variations of individual errors with different time constants. Uncertainties of the model parameters are also taken into account. Performance of the modified KF RAIM is then analyzed with the simulated signals of the global positioning system and navigation with Indian constellation for different phases of aircraft flight. Weighted least squares (WLS) RAIM used for comparison purposes is shown to have lower protection levels. This work, however, is important because KF-based integrity monitors are required to ensure the reliability of advanced navigation methods, such as multi-sensor integration and vector receivers. A key finding of the performance analyses is as follows. Innovation-based tests with an extended KF navigation processor confuse slow ramp faults with residual measurement errors that the filter estimates, leading to missed detection. RAIM with SKF, on the other hand, can successfully detect such faults. Thus, it offers a promising solution to developing KF integrity monitoring algorithms in the range domain. The modified KF RAIM completes processing in time on a low-end computer. Some salient features are also studied to gain insights into its working principles.

Precise Point Positioning using Multi-Constellation GNSS Observations for Kinematic Applications

2015 ◽  
Vol 9 (1) ◽  
Author(s):  
Mahmoud Abd Rabbou ◽  
Ahmed El-Rabbany
Keyword(s):  
Urban Areas ◽  
Precise Point Positioning ◽  
Global Navigation Satellite Systems ◽  
Test Scenario ◽  
Satellite Systems ◽  
Satellite Geometry ◽  
Point Positioning ◽  
Kinematic Ppp ◽  
Gnss Measurements ◽  
Global Navigation Satellite

AbstractTraditional precise point positioning (PPP) is commonly based on un-differenced ionosphere-free linear combination of Global Positioning System (GPS) observations. Unfortunately, for kinematic applications, GPS often experiences poor satellite visibility or weak satellite geometry in urban areas. To overcome this limitation, we developed a PPP model, which combines the observations of three global navigation satellite systems (GNSS), namely GPS, GLONASS and Galileo. Both un-differenced and between-satellite single-difference (BSSD) ionosphere-free linear combinations of pseudorange and carrier phase GNSS measurements are processed. The performance of the combined GNSS PPP solution is compared with the GPS-only PPP solution using a real test scenario in downtown Kingston, Ontario. Inter-system biases between GPS and the other two systems are also studied and obtained as a byproduct of the PPP solution. It is shown that the addition of GLONASS observations improves the kinematic PPP solution accuracy in comparison with that of GPS-only solution. However, the contribution of adding Galileo observations is not significant due to the limited number of Galileo satellites launched up to date. In addition, BSSD solution is found to be superior to that of traditional un-differenced model.

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.

Sign in / Sign up

Export Citation Format

Share Document