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Doors in the sky: Detection, localization and classification of aerial vehicles using laser mesh
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Authors: Wahab Khawaja, Ender Ozturk, Ismail Guvenc
Status: Final
Date of publication: 6 December 2021
Published in: ITU Journal on Future and Evolving Technologies, Volume 2 (2021), Issue 2, Pages 139-156
Article DOI : https://doi.org/10.52953/MNPW9383
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 | Abstract:
Stealth technology and Unmanned Aerial Vehicles (UAVs) are expected to dominate current and future aerial warfare. The radar systems at their maximum operating ranges, however, are not always able to detect stealth and small UAVs mainly due to their small radar cross sections and/or low altitudes. In this paper, a novel technique as an alternative to radar technology is proposed. The proposed approach is based on creating a mesh structure of laser beams initiated from aerial platforms towards the ground. The laser mesh acts as a virtual net in the sky. Any aerial vehicle disrupting the path of the laser beams are detected and subsequently localized and tracked. As an additional feature, steering of the beams can be used for increased coverage and improved localization and classification performance. A database of different types of aerial vehicles is created artificially based on Gaussian distributions. The database is used to develop several Machine Learning (ML) models using different algorithms to classify a target. Overall, we demonstrated through simulations that our proposed model achieves simultaneous detection, classification, localization, and tracking of a target. |
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Keywords: Classification, detection, laser, localization, machine learning, mesh, radar cross section, stealth, tracking, unmanned aerial vehicles (UAVs)
Rights: © International Telecommunication Union, available under the CC BY-NC-ND 3.0 IGO license.
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