Robust TOA-Based UAS Navigation under Model Mismatch in GNSS-Denied Harsh Environments

Global Navigation Satellite Systems (GNSS) is the technology of choice for outdoor positioning purposes but has many limitations when used in safety-critical applications such Intelligent Transportation Systems (ITS) and Unmanned Autonomous Systems (UAS). Namely, its performance clearly degrades in harsh propagation conditions and is not reliable due to possible attacks or interference. Moreover, GNSS signals may not be available in the so-called GNSS-denied environments, such as deep urban canyons or indoors, and standard GNSS architectures do not provide the precision needed in ITS. Among the different alternatives, cellular signals (LTE/5G) may provide coverage in constrained urban environments and Ultra-Wideband (UWB) ranging is a promising solution to achieve high positioning accuracy. The key points impacting any time-of-arrival (TOA)-based navigation system are (i) the transmitters’ geometry, (ii) a perfectly known transmitters’ position, and (iii) the environment. In this contribution, we analyze the performance loss of alternative TOA-based navigation systems in real-life applications where we may have both transmitters’ position mismatch, harsh propagation environments, and GNSS-denied conditions. In addition, we propose new robust filtering methods able to cope with both effects up to a certain extent. Illustrative results in realistic scenarios are provided to support the discussion and show the performance improvement brought by the new methodologies with respect to the state-of-the-art.

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Positioning Performance Limits of GNSS Meta-Signals and HO-BOC Signals

Sensors ◽

10.3390/s20123586 ◽

2020 ◽

Vol 20 (12) ◽

pp. 3586 ◽

Cited By ~ 1

Author(s):

Lorenzo Ortega ◽

Daniel Medina ◽

Jordi Vilà-Valls ◽

François Vincent ◽

Eric Chaumette

Keyword(s):

Intelligent Transportation Systems ◽

Single Point ◽

Transportation Systems ◽

Global Navigation Satellite Systems ◽

Performance Limits ◽

Binary Offset Carrier ◽

Ml Estimation ◽

Satellite Systems ◽

Satellite Constellation ◽

The Impact

Global Navigation Satellite Systems (GNSS) are the main source of position, navigation, and timing (PNT) information and will be a key player in the next-generation intelligent transportation systems and safety-critical applications, but several limitations need to be overcome to meet the stringent performance requirements. One of the open issues is how to provide precise PNT solutions in harsh propagation environments. Under nominal conditions, the former is typically achieved by exploiting carrier phase information through precise positioning techniques, but these methods are very sensitive to the quality of phase observables. Another option that is gaining interest in the scientific community is the use of large bandwidth signals, which allow obtaining a better baseband resolution, and therefore more precise code-based observables. Two options may be considered: (i) high-order binary offset carrier (HO-BOC) modulations or (ii) the concept of GNSS meta-signals. In this contribution, we assess the time-delay and phase maximum likelihood (ML) estimation performance limits of such signals, together with the performance translation into the position domain, considering single point positioning (SPP) and RTK solutions, being an important missing point in the literature. A comprehensive discussion is provided on the estimators’ behavior, the corresponding ML threshold regions, the impact of good and bad satellite constellation geometries, and final conclusions on the best candidates, which may lead to precise solutions under harsh conditions. It is found that if the receiver is constrained by the receiver bandwidth, the best choices are the L1-M or E6-Public Regulated Service (PRS) signals. If the receiver is able to operate at 60 MHz, it is recommended to exploit the full-bandwidth Galileo E5 signal. In terms of robustness and performance, if the receiver can operate at 135 MHz, the best choice is to use the GNSS meta-signals E5 + E6 or B2 + B3, which provide the best overall performances regardless of the positioning method used, the satellite constellation geometry, or the propagation conditions.

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An Enhanced UWB-Based Range/GPS Cooperative Positioning Approach Using Adaptive Variational Bayesian Cubature Kalman Filtering

Mathematical Problems in Engineering ◽

10.1155/2015/843719 ◽

2015 ◽

Vol 2015 ◽

pp. 1-8 ◽

Cited By ~ 1

Author(s):

Feng Shen ◽

Guanghui Xu

Keyword(s):

Kalman Filtering ◽

Intelligent Transportation Systems ◽

Ad Hoc ◽

Transportation Systems ◽

Global Navigation Satellite Systems ◽

Extended Kalman Filtering ◽

Precise Position ◽

Variational Bayesian ◽

Satellite Systems ◽

Cooperative Positioning

Precise position awareness is a fundamental requirement for advanced applications of emerging intelligent transportation systems, such as collision warning and speed advisory system. However, the achievable level of positioning accuracy using global navigation satellite systems does not meet the requirements of these applications. Fortunately, cooperative positioning (CP) techniques can improve the performance of positioning in a vehicular ad hoc network (VANET) through sharing the positions between vehicles. In this paper, a novel enhanced CP technique is presented by combining additional range-ultra-wide bandwidth- (UWB-) based measurements. Furthermore, an adaptive variational Bayesian cubature Kalman filtering (AVBCKF) algorithm is proposed and used in the enhanced CP method, which can add robustness to the time-variant measurement noise. Based on analytical and experimental results, the proposed AVBCKF-based CP method outperforms the cubature Kalman filtering- (CKF-) based CP method and extended Kalman filtering- (EKF-) based CP method.

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Robust Filtering Techniques for RTK Positioning in Harsh Propagation Environments

Sensors ◽

10.3390/s21041250 ◽

2021 ◽

Vol 21 (4) ◽

pp. 1250

Author(s):

Daniel Medina ◽

Haoqing Li ◽

Jordi Vilà-Valls ◽

Pau Closas

Keyword(s):

Intelligent Transportation Systems ◽

Robust Statistics ◽

Real Data ◽

Transportation Systems ◽

Global Navigation Satellite Systems ◽

Mixed Integer ◽

Robust Filtering ◽

Precise Positioning ◽

The Impact ◽

Filtering Techniques

Global navigation satellite systems (GNSSs) play a key role in intelligent transportation systems such as autonomous driving or unmanned systems navigation. In such applications, it is fundamental to ensure a reliable precise positioning solution able to operate in harsh propagation conditions such as urban environments and under multipath and other disturbances. Exploiting carrier phase observations allows for precise positioning solutions at the complexity cost of resolving integer phase ambiguities, a procedure that is particularly affected by non-nominal conditions. This limits the applicability of conventional filtering techniques in challenging scenarios, and new robust solutions must be accounted for. This contribution deals with real-time kinematic (RTK) positioning and the design of robust filtering solutions for the associated mixed integer- and real-valued estimation problem. Families of Kalman filter (KF) approaches based on robust statistics and variational inference are explored, such as the generalized M-based KF or the variational-based KF, aiming to mitigate the impact of outliers or non-nominal measurement behaviors. The performance assessment under harsh propagation conditions is realized using a simulated scenario and real data from a measurement campaign. The proposed robust filtering solutions are shown to offer excellent resilience against outlying observations, with the variational-based KF showcasing the overall best performance in terms of Gaussian efficiency and robustness.

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Practical Modeling of GNSS for Autonomous Vehicles in Urban Environments

Sensors ◽

10.3390/s19194236 ◽

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.

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Assessment of the Implementation of GNSS into Gliding

MAD - Magazine of Aviation Development ◽

10.14311/mad.2017.04.01 ◽

2017 ◽

Vol 5 (4) ◽

pp. 6

Author(s):

Tomáš Kubáč ◽

Jakub Hospodka

Keyword(s):

Global Navigation Satellite Systems ◽

Navigation Satellite ◽

Navigation Systems ◽

Satellite Systems ◽

Global Navigation ◽

Global Navigation Satellite ◽

Global Navigation Systems ◽

Usage Preference ◽

Selection Of ◽

Wide Usage

Global navigation satellite systems are increasingly part of our lives and many industries including aviation. Glider flying is no exception in this trend. Global navigation satellite systems were part of gliding since the early 1990s. First as official recording devices for simple evidence of sporting performances, then as navigation systems, anti-collision systems and emergency location transmitters. Development of recording application was initiated and supported by International Gliding Commission of World Air Sports Federation in way of certifications for flight recorders. The use of navigation and other modern instruments in gliders has brought many benefits but also risks. However, the advantages outweigh the disadvantages and these systems are now integral part of gliding. With this wide usage of global navigation satellite systems devices, there is great many possibilities how and in which way one can use these systems. Pilots must orient themselves in varied selection of products, which they can use to choose one solution, that fits him. Therefore, to find out how and if pilots use these devices, we created questionnaire survey among 143 Czech glider pilots. We found out, that 84% of them are using global navigation satellite systems devices for official record of flight and for navigation as well. More than half of pilots is using free, not built-in devices. Most common devices are mobile phones up to 5 inches of screen diagonal in combination with approved flight recorder without display. If pilots use mobile device for navigation, 52% of them is using one with Windows Mobile operating system, 33% use Android. Navigational software on these mobile devices is then almost tied between SeeYou Mobile, XCSoar and LK8000. Knowledge about usage preference of global navigation systems devices should help pilots with selection and overall orientation in subject.

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

Remote Sensing ◽

10.3390/rs13224525 ◽

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.

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Potential Using Vehicle to Vehicle Communication Based on Wireless Fidelity (Wi-Fi) for Supporting Intelligent Transportation Systems (ITS)

ARID International Journal for Science and Technology ◽

10.36772/arid.aijst.2021.483 ◽

2021 ◽

pp. 61-76

Author(s):

إسراء عصام بن موسى ◽

عبدالسلام صالح الراشدي

Keyword(s):

Intelligent Transportation Systems ◽

Ad Hoc ◽

Real Life ◽

Intelligent Transportation ◽

Transportation Systems ◽

The Road ◽

Vehicle Communication ◽

Vehicle To Vehicle ◽

Vehicle To Vehicle Communication ◽

Wireless Fidelity

Vehicular Ad-hoc Network (VANET) becomes one of the most popular modern technologies these days, due to its contribution to the development and modernization of Intelligent Transportation Systems (ITS). The primary goal of these networks is to provide safety and comfort for drivers and passengers in roads. There are many types of VANET that are used in ITS, in this paper, we particularly focus on the Vehicle to Vehicle communication (V2V), which each vehicle can exchange information to inform drivers of other vehicles about the current state of the road flow, in the event of any emergency to avoid accidents, and reduce congestion on roads. We proposed V2V using Wi-Fi (wireless fidelity); the reason of its unique characteristics that distinguish it from other types. There are many difficulties and the challenges in implementing most types of V2V, and the reason is due to the lack of devices and equipment needed for real implementation. To prove the possibility of applying this type in real life, we made a prototype contains a modified toy car, a 12-volt power supply, sensors, visual, audible alarm, a visual “LED” devices, and finally a 12-volt DC relay unit. As a conclusion, the proposed implementation in spite of minimal requirements and use simple equipment, we have achieved the most important main objectives of the paper: preventing vehicles from collision, early warning, and avoiding congestion on the roads.

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Co-location of SLR and GNSS techniques onboard Galileo and GLONASS satellites

10.5194/egusphere-egu21-7142 ◽

2021 ◽

Author(s):

Grzegorz Bury ◽

Krzysztof Sośnica ◽

Radosław Zajdel ◽

Dariusz Strugarek ◽

Urs Hugentobler

Keyword(s):

Orbital Plane ◽

Terrestrial Reference Frame ◽

Global Navigation Satellite Systems ◽

Navigation Systems ◽

Local Ties ◽

Satellite Systems ◽

The Impact ◽

Space Ties ◽

Gnss Observations

All satellites of the Galileo and GLONASS navigation systems are equipped with laser retroreflector arrays for Satellite Laser Ranging (SLR). SLR observations to Global Navigation Satellite Systems (GNSS) provide the co-location of two space geodetic techniques onboard navigation satellites.SLR observations, which are typically used for the validation of the microwave-GNSS orbits, can now contribute to the determination of the combined SLR+GNSS orbits of the navigation satellites. SLR measurements are especially helpful for periods when the elevation of the Sun above the orbital plane (&#946;&#160;angle) is the highest. The quality of Galileo-IOV orbits calculated using combined SLR+GNSS observations improves from 36 to 30 mm for &#946;>&#8201;60&#176; as compared to the microwave-only solution.&#160;Co-location of two space techniques allows for the determination of the linkage between SLR and GNSS techniques in space. Based on the so-called space ties, it is possible to determine the 3D vector between the ground-based co-located SLR and GNSS stations and compare it with the local ties which are determined using the ground measurements. The agreement between local ties derived from co-location in space and ground measurements is at the level of 1 mm in terms of the long-term median values for the co-located station in Zimmerwald, Switzerland.We also revise the approach for handling the SLR range biases which constitute one of the main error sources for the SLR measurements. The updated SLR range biases consider now the impact of not only of SLR-to-GNSS observations but also the SLR observations to LAGEOS and the microwave GNSS measurements. The updated SLR range biases improve the agreement between space ties and local ties from 34 mm to 23&#160;mm for the co-located station in Wettzell, Germany.Co-location of SLR and GNSS techniques onboard navigation satellites allows for the realization of the terrestrial reference frame in space, onboard Galileo and GLONASS satellites, independently from the ground measurements. It may also deliver independent information on the local tie values with full variance-covariance data for each day with common measurements or can contribute to the control of the ground measurements as long as both GNSS and SLR-to-GNSS observations are available.

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A Differential Evolution Based Multiclass Vehicle Detector and Classifier for Urban Environments

International Journal of Swarm Intelligence Research ◽

10.4018/ijsir.2017070102 ◽

2017 ◽

Vol 8 (3) ◽

pp. 19-42 ◽

Cited By ~ 1

Author(s):

Deepak Dawar ◽

Simone A. Ludwig

Keyword(s):

Differential Evolution ◽

Intelligent Transportation Systems ◽

Classification System ◽

Flow Analysis ◽

Transportation Systems ◽

Urban Environments ◽

Vehicle Classification ◽

Discrete Parameter ◽

On The Road ◽

Transportation Agencies

Video analytics is emerging as a high potential area supplementing intelligent transportation systems (ITSs) with wide ranging applications from traffic flow analysis to surveillance. Object detection and classification, as a sub part of a video analytical system, could potentially help transportation agencies to analyze and respond to traffic incidents in real time, plan for possible future cascading events, or use the classification data to design better roads. This work presents a specialized vehicle classification system for urban environments. The system is targeted at the analysis of vehicles, especially trucks, in urban two lane traffic, to empower local transportation agencies to decide on the road width and thickness. The main thrust is on the accurate classification of the vehicles detected using an evolutionary algorithm. The detector is backed by a differential evolution (DE) based discrete parameter optimizer. The authors show that, though employing DE proves expensive in terms of computational cycles, it measurably improves the accuracy of the classification system.

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GNSS Performance Modelling and Augmentation for Urban Air Mobility

Sensors ◽

10.3390/s19194209 ◽

2019 ◽

Vol 19 (19) ◽

pp. 4209 ◽

Cited By ~ 5

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.

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