Reprint

Advanced Technologies for Position and Navigation under GNSS Signal Challenging or Denied Environments

Edited by
May 2023
450 pages
  • ISBN978-3-0365-7630-5 (Hardback)
  • ISBN978-3-0365-7631-2 (PDF)

This is a Reprint of the Special Issue Advanced Technologies for Position and Navigation under GNSS Signal Challenging or Denied Environments that was published in

Engineering
Environmental & Earth Sciences
Summary

Currently, with the popularity of smart devices, assured Position Navigation and Time (PNT) is critical for these devices and some fundamental infrastructures, i.e., the power grid. The Global Navigation Satellite System (GNSS) is dominant in providing PNT information due to its coverage and high accuracy. However, its signals are weak, and it is vulnerable; multipath and None-Line-Of-Signals (NLOS) are the major errors that occur with regard to the GNSS in applications in urban areas. Advanced signal processing methods are expected to improve its resilience and assurance. In addition, the GNSS is fragile to interference and spoofing, which should be emphasized for unmanned systems and smart devices.

This Special Issue aimed to provide a platform for researchers to publish innovative work on the advanced technologies for position and navigation under GNSS signal-challenging or -denied environments. 

Format
  • Hardback
License and Copyright
© 2022 by the authors; CC BY-NC-ND license
Keywords
differential GNSS; DBA; low-cost; combined positioning; multi-sensor fusion; visual point and line feature; SLAM; LiDAR-visual-inertial odometry; forest point cloud; Unmanned Aerial Vehicle (UAV); Terrestrial Laser Scanning (TLS); canopy cover; event camera; feature tracking; intensity/inertial integration; pseudorange positioning; branch and bound; nonlinear least squares; eLoran; trust region reflective algorithm; initialization; LiDAR-inertial odometry; point cloud registration; multi-sensor fusion; visual SLAM; instance segmentation; neural network; pose estimation; GNSS; IMU; urban positioning; fault detection and exclusion; SLAM; LIDAR; multi-sensor fusion; coupling methods; mobile RTK; low-cost GNSS receiver; positioning accuracy; LiDAR data; tree characteristics; terrain conditions; precision forestry; TreeNet; geographic object-based approach; commercial forests; step detection; indoor positioning; unconstrained state; peak detectors; adaptive threshold; variable sliding window; visibility graph; computational geometry; path planning; mapping; tightly-coupled integration; LIDAR-inertial SLAM; rod-shaped and planar feature; sliding-window; graph optimization framework; INS/GNSS integrated navigation; CNN-GRU; CKF; GNSS outage; multi-GNSS; real-time kinematic; maximum correntropy criterion; Kalman filter; wide-lane; ionosphere-free; GNSS/INS; 3D LiDAR; fault detection; localization; integrity assessment; differential GNSS; SLAM; cooperation SLAM; multi robot system; UAV; UGV; map assistance; particle filter; global search algorithm; pedestrian navigation; Simultaneous Localization and Mapping; autonomous driving; localization; high definition map