GNSS (all systems)

Figure_4_Possible_Opener
April 5, 2022

Graphing a Way out of Multipath: Robust Navigation for Autonomous Vehicles and Robots

A factor-graph optimization-based GNSS positioning method uses GNSS pseudorange and Doppler observations to estimate position, velocity, and receiver clock biases. Added constraints on past and current graph nodes of the graph using time-difference observations of the GNSS carrier phase improve the accuracy, and a robust optimization method excludes multipath outliers. Experimental results reduce horizontal positioning error from 5 to 10 meters to 1.37 meters.

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By Inside GNSS
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Brussels-opener
March 30, 2022

Europe Initiates Ambitious SBAS Expansions: Dual-Frequency Multi-Constellation Signals Coming to EGNOS

The European Geostationary Navigation Overlay Service (EGNOS) will soon launch a new maritime solution that will make legacy and costly coastal ground-based augmentation systems redundant. Meanwhile, the next generation EGNOS V3, featuring dual-frequency, multi-constellation (DFMC) services, is set to come online by 2028, once GPS L5 is declared operational.

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By Peter Gutierrez
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Deus in the Machina: Machine-Learning Corrections for Improved Position Accuracy

A novel method for improving the positioning accuracy of GNSS receivers exploits a machine learning (ML) algorithm. The ML model uses the post-fit residuals, which are readily available after the position computation from the position, velocity and timing (PVT) engine, adoptable by existing receivers without requiring any modification. The performance of this method, demonstrated using data collected with mass-market receivers as well as a Google public dataset collected with Android smartphones, shows the practicality of the concept.

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By Inside GNSS
shutterstock_1257663727
March 29, 2022

Q: What is the future of autonomous vehicles?

The concept of autonomous driving has generated a lot of interest and attention in the past decades as it is believed to provide numerous benefits for individuals and society: increased road safety, reduced traffic congestion, accidents and death, and saving time and pollution on commuting. There is a lot of ongoing work on this topic, much research and many experiments have been conducted on how to make cars learn the environment, make human-like decisions and drive on their own.

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By Inside GNSS
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Volpe-logotype-blue-Horizontal
March 28, 2022

Job Opportunity: (SES) Director, Center for Communications, Navigation, Surveillance Systems and Engineering

US Department of Transportation, Cambridge, MA

This position is one of the Technical Centers at Volpe whose function is to undertake transportation analysis, research and system development that contributes to a compelling vision of the 21st Century transportation enterprise and supports decision making in the development, management, operation, and financing or an integrated multimodal national transportation system that meets 21st Century mobility needs for goods and people.

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By Inside GNSS
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