Tracking and prediction of small unmanned aerial vehicles' flight behavior and three-dimensional flight path from laser gated viewing images

Martin Laurenzis; Martin Rebert; Stéphane Schertzer; Frank Christnacher

doi:10.1117/12.2519273

2 May 2019 Tracking and prediction of small unmanned aerial vehicles' flight behavior and three-dimensional flight path from laser gated viewing images

Martin Laurenzis, Martin Rebert, Stéphane Schertzer, Frank Christnacher

Author Affiliations +

Proceedings Volume 11005, Laser Radar Technology and Applications XXIV; 110050D (2019) https://doi.org/10.1117/12.2519273
Event: SPIE Defense + Commercial Sensing, 2019, Baltimore, MD, United States

Abstract

In the last decade, small and mirco unmanned aerial vehicles (MUAV) have become an increasing risk to security and safety in civilian and military scenarios. Further, countermeasures are hard to deploy due to the MUAV ability to operate with highly agile flight maneuver and the physical constrains due to very small cross-sections as well for RADAR as for LiDAR detection. The French-German Research Institute of Saint-Louis (ISL) is studying heterogeneous sensor networks for detection and identification of threats. Shortwave laser gated viewing is used to record images of the target and different image processing algorithms and filters are investigated to perform reliable tracking of MUAV flying in front of textured and clear sky backgrounds. Here, an analysis approach is presented to analyze the MUAV flight behavior and three-dimensional path from image data. Further, a prediction approach is presented to estimate the target position in near future.

Conference Presentation

Citation Download Citation

Martin Laurenzis, Martin Rebert, Stéphane Schertzer, and Frank Christnacher "Tracking and prediction of small unmanned aerial vehicles' flight behavior and three-dimensional flight path from laser gated viewing images", Proc. SPIE 11005, Laser Radar Technology and Applications XXIV, 110050D (2 May 2019); https://doi.org/10.1117/12.2519273

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