Global Navigation Satellite System for Unmanned Aerial Vehicle
A special issue of Aerospace (ISSN 2226-4310).
Deadline for manuscript submissions: closed (31 October 2023) | Viewed by 5271
Special Issue Editors
Interests: GNSS positioning in challenging environments; 3D-mapping-aided GNSS; collaborative positioning; signal propagation modelling; multi-sensor integration; machine-learning-aided positioning; indoor positioning
Interests: GNSS; GNSS-RTK; GNSS NLOS/multipath mitigation in urban canyons LiDAR-aided GNSS positioning; perception-aided GNSS positioning; LiDAR SLAM in challenging dynamic scenes; navigation; autonomous driving; robotics
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Special Issue Information
Dear Colleagues,
With excellent flexibility and mobility, the unmanned aerial vehicle (UAV) has received extensive attention and rapid developments in the last few decades, contributing to various applications, including surveillance, surveying, and future intelligent transportation systems. The effectiveness of those applications greatly relies on the performance of the onboard positioning system. UAV positioning is usually achieved by the global navigation satellite system (GNSS) due to its wide availability of service, absolute positioning with sufficient accuracy, and acceptable cost for the mass market. With the increasing trend of using UAVs for civil applications, there are new demands on their GNSS performance. The positioning solution is required to be accurate and precise, even for urban areas, where the multipath and non-line-of-sight signal receptions are challenging for GNSS. In addition, the reliability of GNSS has also attracted concerns about guaranteeing the safe operation of UAVs, especially with the recent security threats from spoofing. The development of UAVs onboard GNSS also enables its integration with cutting-edge technologies from other research fields.
This Special Issue invites recent contributions related to the different aspects of GNSS for UAVs, including but not limited to: positioning in challenging environments, advanced estimation techniques, filtering and optimization methods for positioning such as Kalman filter and factor graph optimization, fault detection and exclusion, GNSS precise positioning, signal propagation modelling and simulation, cooperative positioning, machine learning or deep-learning-aided GNSS, GNSS-involved multi-sensor integrated system, GNSS-integrated simultaneous localization and mapping (SLAM), GNSS-related UAV control or path planning, GNSS spoofing detection, and other cutting-edge techniques such as 3D-mapping-aided GNSS.
Dr. Guohao Zhang
Dr. Weisong Wen
Guest Editors
Manuscript Submission Information
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Keywords
- UAV
- GNSS
- urban positioning
- multipath
- Kalman filter
- factor graph
- fault detection and isolation
- precise positioning
- simultaneously localization and mapping (SLAM)
- cooperative positioning
- machine learning
- multi-sensor integration
- spoofing detection
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