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The stealth technology and unmanned aerial vehicles (UAVs) are expected todominate current and future aerial warfare. The radar systems at their maximumoperating ranges, however, are not always able to detect stealth and small UAVsmainly due to their small radar cross-sections and/or low altitudes. In thispaper, a novel technique as an alternative to radar technology is proposed. Theproposed approach is based on creating a mesh structure of laser beamsinitiated from aerial platforms towards the ground. The laser mesh acts as avirtual net in the sky. Any aerial vehicle disrupting the path of the laserbeams are detected and subsequently localized and tracked. As an additionalfeature, steering of the beams can be used for increased coverage and improvedlocalization and classification performance. A database of different types ofaerial vehicles is created artificially based on Gaussian distributions. Thedatabase is used to develop several machine learning (ML) models usingdifferent algorithms to classify a target. Overall, we demonstrated throughsimulations that our proposed model achieves simultaneous detection,classification, localization, and tracking of a target.

Doors in the Sky: Detection, Localization and Classification of Aerial Vehicles using Laser Mesh