Urban Air Mobility (UAM) presents a promising solution to urban traffic congestion, offering fast and efficient travel within cities. However, safety concerns persist, particularly regarding adverse weather conditions like Clear Air Turbulence (CAT), which can pose risks to UAM flights. Current weather detection instruments have limitations, especially in detecting water-free CAT. This study proposes using LiDAR technology with Optical Orthogonal Frequency Division Multiple Access (OOFDMA) and a Risley prism to detect CATs by analyzing the movement of urban dust affected by CAT-generated airflow. The LiDAR’s ability to rapidly rotate, send multiple laser wavelengths and accurately measure distances ensures precise detection of obstacles, including CATs. Computational Fluid Dynamics (CFD) modeling validates the LiDAR’s efficacy in distinguishing between CAT and non-CAT scenarios. By analyzing reflected waves from dust movements, LiDAR reliably identifies CATs, providing a robust solution for UAM safety in urban environments.
Detecting clear air turbulence in urban air mobility by using LiDAR with OOFDMA and a Risley prism
Electro-Optical and Infrared Systems: Technology and Applications XXI ; 2024 ; Edinburgh, United Kingdom
Proc. SPIE ; 13200
01.11.2024
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
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