Methodology for Simulating 5G and GNSS High-Accuracy Positioning

Peral-Rosado, José A. del; Saloranta, Jani; Destino, Giuseppe; López-Salcedo, José A.; Seco-Granados, Gonzalo

doi:10.3390/s18103220

Cited by 34 publications

(14 citation statements)

References 15 publications

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“…Fusion of GNSS and 5G in urban areas Due to the fact that GNSS may have a downgraded accuracy in urban canyons caused by limited satellite availability, unfavorable satellite geometry and multiple multipath, a fusion of the 5G cm-wave with GNSS might result in higher positioning accuracies (Peral-Rosado et al 2018 ). Therefore, compatibility and interoperability of 5G and GNSS is necessary.…”

Section: New Opportunities and Perspectivesmentioning

confidence: 99%

Status, perspectives and trends of satellite navigation

Hein

2020

Satell Navig

148

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This paper reviews the status of satellite navigation (as per 11 May 2020)—without claim for completeness—and discusses the various global navigation satellite systems, regional satellite navigation systems and satellite-based augmentation systems. Problems and challenges for delivering nowadays a safe and reliable navigation are discussed. New opportunities, perspectives and megatrends of satellite navigation are outlined. Some remarks are closing this paper emphasizing the great value of satellite navigation at present and in future.

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Section: New Opportunities and Perspectivesmentioning

confidence: 99%

Status, perspectives and trends of satellite navigation

Hein

2020

Satell Navig

148

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“…Um ponto interessante é a integração do 5G com o GNSS em áreas urbanas, devido ao posicionamento por GNSS ter sua acurácia deteriorada devido à disponibilidade limitada de sinais e multicaminho. Assim, tal integração pode resultar em posicionamento mais acurado (PERAL-ROSADO et al, 2018), mas, ainda, é necessária a compatibilidade e interoperabilidade entre o 5G e o GNSS.…”

Section: Tendências E Desafios No Posicionamento Multi-gnssunclassified

Posicionamento multi-GNSS

Júnior

Silva

Júnior³

et al. 2020

Rev. Bras. Cartogr.

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Os GNSS (Global Navigation Satellite Systems) têm ganhado bastante visibilidade nas últimas duas décadas, sendo atualmente aplicados em diversas atividades, as quais vão muito além do posicionamento e navegação; algumas delas requerem alta acurácia (centimétrica a milimétrica), como o monitoramento de estruturas e a agricultura de precisão. Para atender a estas necessidades, diferentes métodos de posicionamento foram desenvolvidos, como o posicionamento por ponto (simples e preciso) e o posicionamento relativo. Mais recentemente, surgiu a possibilidade do posicionamento em tempo real com uso de redes, tanto para o posicionamento por ponto quanto para o relativo. O lançamento de novas constelações globais de satélites tem permitido a integração dos diferentes sistemas que, quando bem-sucedida, oferece melhorias para o posicionamento quanto à disponibilidade de satélites, à geometria entre o receptor e o satélite, à solução das ambiguidades e o desempenho deste quando comparado ao uso isolado dos sistemas. Nesse sentido, este artigo tem por objetivo apresentar uma revisão e o estado da arte das principais características dos quatro sistemas globais e dos diferentes métodos de posicionamento, dando destaque para a integração multi-GNSS, tendências e desafios em cada um deles. São também apresentados resultados comparando o posicionamento GPS ao posicionamento multi-GNSS com as quatro constelações e uso de uma máscara de elevação de 25°, simulando um ambiente obstruído. Com relação à acurácia do posicionamento, que leva em consideração o erro e desvio-padrão na estimativa da posição, a integração dos sistemas trouxe uma melhoria de até 44%.

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“…Apart from GNSS-based, DGNSS-based, and RTK-based vehicle-localization methods as described in the present work, many other approaches with different measurement uncertainties could also be used to measure positioning and velocity of vehicles, e.g. 5G-based vehicle localization is a new promising high-precision positioning method in the last few years [28]. And the influence of their measurement uncertainties could also be evaluated using the proposed required safe distance and other indexes as shown in Section 4.…”

Section: Vehicle-localization Precisionsmentioning

confidence: 99%

Vehicle‐localization‐based and DSRC‐based autonomous vehicle rear‐end collision avoidance concerning measurement uncertainties

Chen

Zhan

et al. 2019

IEEJ Transactions Elec Engng

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Rear‐end collision is one of the most serious accidents for vehicles, some rear end collision avoidance systems have been developed to protect vehicles from rear‐end collisions. Current rear‐end collision avoidance systems mainly utilize vehicle‐relative measurement sensors to acquire information on surrounding vehicles, considering limited detection ranges and impaired performance in bad weathers of these vehicle sensors, currently used collision avoidance systems cannot guarantee vehicle safety in all environments. Vehicle‐localization‐based and intervehicle communication‐based rear‐end collision avoidance approaches can be possible solutions to improve vehicle safety compared with present vehicle sensor‐based collision avoidance systems. Dedicated Short‐Range Communication (DSRC) is introduced to transfer information on surrounding vehicles instead of using vehicle‐relative measurement sensors. Vehicle dynamic model and brake system dynamics are used to generate precise vehicle states that would be used in rear‐end collision avoidance. Required safe distance is used as the safety index when using different vehicle‐localization methods with a predefined safety probability of 99.99%. Monte Carlo simulations are executed to evaluate the influence of measurement uncertainties. Simulation results show that vehicle‐localization‐based and DSRC‐based rear‐end collision avoidance methods can guarantee vehicles free from rear‐end collision and expand the service capabilities of velocity compared with the traditional vehicle radar‐based rear‐end collision avoidance method. Evaluation outcomes encourage us to adopt a more precise absolute vehicle‐localization approach in rear‐end collision avoidance, because required safe distance and safe distance margin can be decreased when using a high‐precision vehicle‐localization method compared with standalone GNSS‐based localization. Some further aspects are discussed in this work that need to be tackled with to make vehicle‐localization‐based and intervehicle communication‐based rear‐end collision avoidance systems into practice, including real‐time brake system dynamics acquirement, benefit of DSRC to curve roads, and so on. © 2019 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

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Methodology for Simulating 5G and GNSS High-Accuracy Positioning

Cited by 34 publications

References 15 publications

Status, perspectives and trends of satellite navigation

Status, perspectives and trends of satellite navigation

Posicionamento multi-GNSS

Vehicle‐localization‐based and DSRC‐based autonomous vehicle rear‐end collision avoidance concerning measurement uncertainties

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