Reprint

GNSS, Space Weather and TEC Special Features

Edited by
June 2023
332 pages
  • ISBN978-3-0365-7594-0 (Hardback)
  • ISBN978-3-0365-7595-7 (PDF)

This book is a reprint of the Special Issue GNSS, Space Weather and TEC Special Features that was published in

Engineering
Environmental & Earth Sciences
Summary

In the domain of electronic navigation, satellite navigation (GNSS) is one of the most important complex modern systems. GNSS is a key aspect of infrastructure which supports the development and improvement of power grid systems, banking operations, global transportation systems, and global communication systems. Today, GNSS requires the use of several positioning networks and sensors, such as radio networks and MEMS. The Earth’s atmosphere, particularly the ionosphere and troposphere, can be seen as a huge laboratory where multiple processes and phenomena directly affecting the propagation of EM waves occur. Like all complex systems, GNSS technology has also gone through certain evolutionary stages. Factors affecting the future evolution of GNSS technology include the appearance of new signals and frequencies, complementary technologies in use, etc., but in the domain of GNSS technologies, it is essential to study the impact of space weather on GNSS systems. A key part of research related to GNSS technologies is the vertical TEC distribution and anomalies related to earthquakes and volcanic eruptions on Earth. There are many challenges that need to be addressed because they affect reliability, accuracy, and all other essential parameters of GNSS systems. It addresses some of these issues by publishing manuscripts which study GNSS risk assessment, different effects of space weather disturbances on the operation of GNSS systems, environmental impacts on the operation of GNSS systems, GNSS positioning error budgets, TEC special features in volcano eruptions, and similar topics.

Format
  • Hardback
License
© by the authors
Keywords
ionosphere; volcanic activity; total electron content; ground-truth data; seismo-ionospheric coupling; GNSS time series analysis; landslide displacement prediction; attention mechanism; deep learning; South Atlantic Anomaly; radiation measurement; CubeSat observation; radiation belts; Ni-based superalloys; international space station; microstructure; morphology; fractal reconstruction; Fractal Hausdorff dimension; GNSS-IR; snow depth; signal-to-noise ratio; multi-GNSS; multi-frequency; mean fusion; navigation positioning system; positioning accuracy; reliability method; Global Positioning System (GPS); Differential Global Positioning System (DGPS); European Geostationary Navigation Overlay Service (EGNOS); TEC; detrending; Savitzky–Golay; polynomial; lightning; GPS TEC; EIA; diurnal evolution; seasonal variation; spatiotemporal analysis; landslide displacement prediction; attribute-augmented; deep learning; equatorial and low-latitude ionosphere; ionospheric irregularity; scintillation; radio occultation observation; COSMIC; ionogram; GPS/GNSS; Global Navigation Satellite Systems (GNSS); Continuously Operating Reference Station (CORS); Precise Point Positioning (PPP); ionospheric corrections; ionospheric model; GNSS-IR; soil moisture content; multisatellite combination; dual-frequency pseudorange; dual-frequency carrier phase combination; multipath error; phase delay; GNSS; lightning; ROTI; gravity wave; daytime; nighttime; PCC; GNSS; GPS; antenna; calibration; EPN; GNSS meteorology; water vapor; tomography; multi-GNSS; TEC; ionosphere; seismic swarm; lithosphere-atmosphere-ionosphere coupling; CID; GNSS; tropospheric error; surface meteorological data; statistical position equilibrium; Saastamoinen model of zenith tropospheric delay; n/a