B: Applications

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May 24, 2022

Q: What commitments have the various constellation providers made to GNSS users regarding the integrity of their signals and services? How are these commitments transmitted to users, and how can they be updated if circumstances require?

A: GNSS users who must verify the integrity of their navigation solutions to meet safety requirements need at least some knowledge of the degree to which they can trust the signals received from GNSS satellites before additional monitoring is added.

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By Inside GNSS
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May 23, 2022

The ionospheric scintillation phenomenon

The SAGAIE network was deployed in West-Africa in 2013 to assess the feasibility of an equatorial for ASECNA SBAS by studying ionospheric scintillation. This study of the network’s measurements, taken between 2013 and 2016, analyzes the characteristics of the scintillation recorded by five receivers that cover Sub-Saharan West-Africa.

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By Inside GNSS
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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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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
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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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Multiple Imaging Radars Integrate with INS/GNSS via AUTO Software Reliable and Accurate Positioning for Autonomous Vehicles and Robots

Difficult GNSS environments and adverse weather conditions require a fusion of many sensors to maintain lane-level accuracy for autonomous platforms, without incurring high costs that would inhibit widespread adoption. Radars are an attractive option in a multi-sensor integration scheme due to being robust to adverse weather and insensitive to lighting variations.

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By Inside GNSS
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