A Cooperative Positioning Scheme Based on Beam-Forming for Intelligent Transportation Systems

2014 ◽  
Vol 945-949 ◽  
pp. 3255-3259 ◽  
Author(s):  
Lei Du ◽  
Nan Liu ◽  
Rui Fang ◽  
Nan Li ◽  
Xiang Hui Song
Keyword(s):  
Wireless Communication ◽  
Intelligent Transportation Systems ◽  
Vehicular Networks ◽  
Least Squares Method ◽  
Satellite System ◽  
Transportation Systems ◽  
Beam Forming ◽  
Main Process ◽  
Cooperative Positioning ◽  
Global Navigation Satellite

Cooperative positioning (CP) originating in wireless sensor networks (WSN) is expected to enhance the accuracy of real-time positioning by exchanging location related information in vehicular network via wireless communication. A novel CP system based on beam-forming for vehicular networks is proposed by this work. Its application includes several roadside units equipped with a kind of transceiver based on an special dual-transmitter outphasing architecture which are utilized to broadcast the spatial directivity and correct receive angle information to vehicles with onboard wireless communication units in desired areas. The goal of enhancement positioning via vehicle-to-infrastructure communication can be acquired by a data fusion means based on the extended Kalman filter when GNSS is available and a cooperative solution based on the least-squares method under the condition that the global navigation satellite system (GNSS) is available respectively. The main process of positioning and all the key technical points of the system's application are modeled and analyzed mathematically. And the results of computer simulation confirm the technical practicability for the proposed method.

A Cooperative Positioning Scheme Based on Extended Kalman Filter for Curve Warning Systems

2014 ◽  
Vol 915-916 ◽  
pp. 1189-1193 ◽  
Author(s):  
Lei Du ◽  
Nan Liu ◽  
Rui Fang ◽  
Xiang Hui Song
Keyword(s):  
Kalman Filter ◽  
Extended Kalman Filter ◽  
Intelligent Transportation Systems ◽  
Black Spot ◽  
Satellite System ◽  
Transportation Systems ◽  
Cooperative Positioning ◽  
Roadside Unit ◽  
Time Position ◽  
Global Navigation Satellite

Cooperative positioning (CP) is one of the core features in intelligent transportation systems (ITS) which is used to increase the positioning accuracy via wireless communication between vehicles and infrastructures. The global navigation satellite system (GNSS) is always unavailable near black spot such as the curve which needs to be solved. So, in this paper, a novel CP scheme is proposed for the curve warning scenario with limited GNSS by utilizing the information of received signal strength and pointer angular of the roadside unit which is in a special dual-transmitter outphasing architecture. An extended Kalman filter is founded to estimate the real-time position of the vehicle in the curve section. The whole warning scenario is analyzed by computer simulation, and the result shows the feasibility of the method.

scholarly journals Improvement of Anomalous Behavior Detection of GNSS Signal Based on TDNN for Augmentation Systems

Sensors ◽  
2018 ◽  
Vol 18 (11) ◽  
pp. 3800 ◽  
Author(s):  
Daehee Kim ◽  
Jeongho Cho
Keyword(s):  
Intelligent Transportation Systems ◽  
Satellite System ◽  
Anomalous Behavior ◽  
Transportation Systems ◽  
Civil Aviation ◽  
Integrity Monitoring ◽  
Delayed Neural Networks ◽  
Stringent Performance ◽  
Integrity Assurance ◽  
Global Navigation Satellite

The reliability of a navigation system is crucial for navigation purposes, especially in areas where stringent performance is required, such as civil aviation or intelligent transportation systems (ITSs). Therefore, integrity monitoring is an inseparable part of safety-critical navigation applications. The receiver autonomous integrity monitor (RAIM) has been used with the global navigation satellite system (GNSS) to provide integrity monitoring within avionics itself, such as in civil aviation for lateral navigation (LNAV) or the non-precision approach (NPA). However, standard RAIM may not meet the stricter aviation availability and integrity requirements for certain operations, e.g., precision approach flight phases, and also is not sufficient for on-ground vehicle integrity monitoring of several specific ITS applications. One possible way to more clearly distinguish anomalies in observed GNSS signals is to take advantage of time-delayed neural networks (TDNNs) to estimate useful information about the faulty characteristics, rather than simply using RAIM alone. Based on the performance evaluation, it was determined that this method can reliably detect flaws in navigation satellites significantly faster than RAIM alone, and it was confirmed that TDNN-based integrity monitoring using RAIM is an encouraging alternative to improve the integrity assurance level of RAIM in terms of GNSS anomaly detection.

Information Fusion for Localization Within Vehicular Networks

2011 ◽  
Vol 64 (3) ◽  
pp. 401-416 ◽  
Author(s):  
Mahmoud Efatmaneshnik ◽  
Allison Kealy ◽  
Asghar Tabatabei Balaei ◽  
Andrew G. Dempster
Keyword(s):  
Intelligent Transportation Systems ◽  
Vehicular Networks ◽  
Transportation Systems ◽  
Cooperative Positioning ◽  
Dedicated Short Range Communications ◽  
Location Determination ◽  
Moving Vehicles ◽  
Map Data ◽  
Safety Applications ◽  
Navigation Information

Cooperative positioning (CP) is a localization technique originally developed for use across wireless sensor networks. With the emergence of Dedicated Short Range Communications (DSRC) infrastructure for use in Intelligent Transportation Systems (ITS), CP techniques can now be adapted for use in location determination across vehicular networks. In vehicular networks, the technique of CP fuses GPS positions with additional sensed information such as inter-vehicle distances between the moving vehicles to determine their location within a neighbourhood. This paper presents the results obtained from a research study undertaken to demonstrate the capabilities of DSRC for meeting the positioning accuracies of road safety applications. The results show that a CP algorithm that fully integrates both measured/sensed data as well as navigation information such as map data can meet the positioning requirements of safety related applications of DSRC (<0·5 m). This paper presents the results of a Cramer Rao Lower Bound analysis which is used to benchmark the performance of the CP algorithm developed. The Kalman Filter (KF) models used in the CP algorithm are detailed and results obtained from integrating GPS positions, inter-vehicular ranges and information derived from in-vehicle maps are then discussed along with typical results as determined through a variety of network simulation studies.

scholarly journals A Proposal of a Troposphere Model in a GNSS Simulator for VANET Applications

Sensors ◽  
2021 ◽  
Vol 21 (7) ◽  
pp. 2491
Author(s):  
Mauro Tropea ◽  
Angelo Arieta ◽  
Floriano De Rango ◽  
Francesco Pupo
Keyword(s):  
Intelligent Transportation Systems ◽  
Autonomous Vehicles ◽  
Weather Conditions ◽  
Propagation Delay ◽  
Satellite System ◽  
Transportation Systems ◽  
Navigation Systems ◽  
Vehicle Positioning ◽  
Satellite Navigation Systems ◽  
Global Navigation Satellite

Vehicle positioning is becoming an important issue related to Intelligent Transportation Systems (ITSs). Novel vehicles and autonomous vehicles need to be localized under different weather conditions and it is important to have a reliable positioning system to track vehicles. Satellite navigation systems can be a key technology in providing global coverage and providing localization services through many satellite constellations such as GPS, GLONASS, Galileo and so forth. However, the modeling of positioning and localization systems under different weather conditions is not a trivial objective especially considering different factors such as receiver sensitivity, dynamic weather conditions, propagation delay and so forth. This paper focuses on the use of simulators for performing different kinds of tests on Global Navigation Satellite System (GNSS) systems in order to reduce the cost of the positioning testing under different techniques or models. Simulation driven approach, combined with some specific hardware equipment such as receivers and transmitters can characterize a more realistic scenario and the simulation can consider other aspects that could be complex to really test. In this work, the main contribution is the introduction of the Troposphere Collins model in a GNSS simulator for VANET applications, the GPS-SDR-SIM software. The use of the Collins model in the simulator allows to improve the accuracy of the simulation experiments throughout the reduction of the receiver errors.

scholarly journals A Robust Cubature Kalman Filter with Abnormal Observations Identification Using the Mahalanobis Distance Criterion for Vehicular INS/GNSS Integration

Sensors ◽  
2019 ◽  
Vol 19 (23) ◽  
pp. 5149 ◽  
Author(s):  
Bingbing Gao ◽  
Gaoge Hu ◽  
Xinhe Zhu ◽  
Yongmin Zhong
Keyword(s):  
Kalman Filter ◽  
Mahalanobis Distance ◽  
Intelligent Transportation Systems ◽  
System Integration ◽  
Satellite System ◽  
Transportation Systems ◽  
Scaling Factor ◽  
Cubature Kalman Filter ◽  
Noise Covariance ◽  
Global Navigation Satellite

INS/GNSS (inertial navigation system/global navigation satellite system) integration is a promising solution of vehicle navigation for intelligent transportation systems. However, the observation of GNSS inevitably involves uncertainty due to the vulnerability to signal blockage in many urban/suburban areas, leading to the degraded navigation performance for INS/GNSS integration. This paper develops a novel robust CKF with scaling factor by combining the emerging cubature Kalman filter (CKF) with the concept of Mahalanobis distance criterion to address the above problem involved in nonlinear INS/GNSS integration. It establishes a theory of abnormal observations identification using the Mahalanobis distance criterion. Subsequently, a robust factor (scaling factor), which is calculated via the Mahalanobis distance criterion, is introduced into the standard CKF to inflate the observation noise covariance, resulting in a decreased filtering gain in the presence of abnormal observations. The proposed robust CKF can effectively resist the influence of abnormal observations on navigation solution and thus improves the robustness of CKF for vehicular INS/GNSS integration. Simulation and experimental results have demonstrated the effectiveness of the proposed robust CKF for vehicular navigation with INS/GNSS integration.

scholarly journals A Survey on Fault Tolerance Techniques for Wireless Vehicular Networks

Electronics ◽  
2019 ◽  
Vol 8 (11) ◽  
pp. 1358 ◽  
Author(s):  
João Almeida ◽  
João Rufino ◽  
Muhammad Alam ◽  
Joaquim Ferreira
Keyword(s):  
Fault Tolerance ◽  
Intelligent Transportation Systems ◽  
Vehicular Networks ◽  
Road Traffic ◽  
Fault Tolerant ◽  
Human Life ◽  
Transportation Systems ◽  
Vehicular Communications ◽  
Self Driving Cars ◽  
Meta Analyses

Future intelligent transportation systems (ITS) hold the promise of supporting the operation of safety-critical applications, such as cooperative self-driving cars. For that purpose, the communications among vehicles and with the road-side infrastructure will need to fulfil the strict real-time guarantees and challenging dependability requirements. These safety requisites are particularly important in wireless vehicular networks, where road traffic presents several threats to human life. This paper presents a systematic survey on fault tolerance techniques in the area of vehicular communications. The work provides a literature review of publications in journals and conferences proceedings, available through a set of different search databases (IEEE Xplore, Web of Science, Scopus and ScienceDirect). A systematic method, based on the preferred reporting items for systematic reviews and meta-analyses (PRISMA) Statement was conducted in order to identify the relevant papers for this survey. After that, the selected articles were analysed and categorised according to the type of redundancy, corresponding to three main groups (temporal, spatial and information redundancy). Finally, a comparison of the core features among the different solutions is presented, together with a brief discussion regarding the main drawbacks of the existing solutions, as well as the necessary steps to provide an integrated fault-tolerant approach to the future vehicular communications systems.

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