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Artificial Intelligence for Wake Vortex Detection and Characterization in LiDAR Scans

Contact: Michael Färber

Project Status: active


Wake vortices are air turbulence generated by aircraft that can be dangerous for following aircraft. Minimum distances between landing aircraft are therefore necessary, but limit runway capacity. Real-time monitoring of wake vortices in the glide path could help reduce minimum separation distances and increase runway capacity. Currently, there is a lack of methods to automatically characterize wake vortices with high accuracy in real time. The goal of this project is to automatically detect and characterize wake vortices in LiDAR measurements using artificial intelligence (AI), provide reliable evaluation and error estimation, and use simulation data as a training dataset. A reliable method for evaluating LiDAR measurements would be a major step toward dynamic separations, making aircraft landings safer, more efficient, and ultimately more environmentally and climate friendly. You can find more information on the poster for the Helmholtz AI Conference 2023.

Involved Persons
Michael Färber, Shuzhou Yuan, Zhan Qu


from: 1 Januar 2023
until: 30 Juni 2024
Funding: BMVI



Research Group

Web Science

Area of Research

Knowledge Discovery, Data Mining, Artificial Intelligence, Data Science

Publications Belonging to the Project
 - inproceedings
 - book
 - incollection
 - booklet
 - proceedings
 - phdthesis
 - techreport
 - deliverable
 - manual
 - misc
 - unpublished