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.

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 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.

An Evaluation of the Increase in the Quality and Quantity of Navigational Information Available from Low-Frequency Radio Navigation Systems

1999 ◽  
Vol 52 (3) ◽  
pp. 411-417
Author(s):  
Victor Filin
Keyword(s):  
Coastal Waters ◽  
Low Cost ◽  
Low Frequency ◽  
High Accuracy ◽  
Global Navigation Satellite Systems ◽  
Navigation Satellite ◽  
Navigation Systems ◽  
Satellite Systems ◽  
Radio Navigation ◽  
Global Navigation Satellite

Low frequency radio navigation systems continue to play an important role in the provision of precise navigation for vessels sailing in coastal waters, and in other zones requiring high accuracy. Modernization of the existing Loran C chains, and deployment of new ones, shows there is strong interest in these systems despite the appearance of global navigation satellite systems (GNSS) such as ‘Navstar’ and ‘Glonass’. This continuation of interest is connected to the relatively low cost of operation of the systems, the low cost of receiver-indicators and the need to provide users with very precise but reliable positioning information, which at present can only be obtained by joint use of GNSS and Loran C. To make the most of such an approach, Loran C should provide accuracy and reliability similar to GNSS.

GNSS Positioning Enhancement Based on NLOS Multipath Biases Estimation Using Gaussian Mixture Noise

2021 ◽  
pp. 632-652
Author(s):  
Guermah Bassma ◽  
Sadiki Tayeb ◽  
El Ghazi Hassan
Keyword(s):  
Em Algorithm ◽  
Statistical Tests ◽  
Hybrid Approach ◽  
Gaussian Mixture ◽  
High Accuracy ◽  
Global Navigation Satellite Systems ◽  
Positioning System ◽  
Satellite Systems ◽  
Global Positioning ◽  
Global Navigation Satellite

Global navigation satellite systems (GNSS) have been widely used in many applications where positioning plays an important role. However, the performances of these applications can be degraded in urban canyons, due to Non-Line-Of-Sight (NLOS) and Multipath interference affecting GNSS signals. In order to ensure high accuracy positioning, this article proposes to model the NLOS and Multipath biases by Gaussian Mixture noise using Expectation Maximization (EM) algorithm. In this context, an approach to estimate the Multipath and NLOS biases for real time positioning is presented and statistical tests for searching the probability distribution of NLOS and Multipath biases are illustrated. Furthermore, a hybrid approach based on PF (Particle Filter) and EM algorithm for estimating user position in hard environment is presented. Using real GPS (Global Positioning System) signal, the efficiency of the proposed approach is shown, and a significant improvement of the positioning accuracy over the simple PF estimation is obtained.

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 A High-Accuracy GNSS Dataset of Ground Truth Points Collected within Îles-de-Boucherville National Park, Quebec, Canada

Data ◽  
2021 ◽  
Vol 6 (3) ◽  
pp. 32
Author(s):  
Kathryn Elmer ◽  
Margaret Kalacska
Keyword(s):  
National Park ◽  
Hyperspectral Imagery ◽  
Ground Truth ◽  
High Accuracy ◽  
Global Navigation Satellite Systems ◽  
Validation Data ◽  
Ground Truth Data ◽  
Satellite Systems ◽  
Study Sites ◽  
Global Navigation Satellite

A new ground truth dataset generated with high-accuracy Global Navigation Satellite Systems (GNSS) positional data of the invasive reed Phragmites australis subsp. australis within Îles-de-Boucherville National Park (Quebec, Canada) is described. The park is one of five study sites for the Canadian Airborne Biodiversity Observatory (CABO) and has stands of invasive P. australis spread throughout the park. Previously, within the context of CABO, no ground truth data had been collected within the park consolidating the locations of P. australis. This dataset was collected to serve as training and validation data for CABO airborne hyperspectral imagery acquired in 2019 to assist with the detection and mapping of P. australis. The locations of the ground truth points were found to be accurate within one pixel of the hyperspectral imagery. Overall, 320 ground truth points were collected, representing 158 locations where P. australis was present and 162 locations where it was absent. Auxiliary data includes field photographs and digitized field notes that provide context for each point.

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