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10 October 2019 Active and passive computational imaging for tracking and prediction of three-dimensional MUAV flight paths
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Abstract
Micro unmanned aerial vehicles (MUAV) have become increasingly popular during the last decade due to their access to a wide consumer market. With the increasing number of MUAV, the unintended and intended misuse by flying close to sensitive areas has risen as a potentially increasing risk. To counter this threat, surveillance systems are under development which will monitor the MUAV flight behavior. In this context, the reliable tracking and prediction of the MUAV flight behavior is crucial to increase the performance of countermeasures. In this paper, we discuss electro-optical computational imaging methods with a focus on the ability to perform a tracking of the three dimensional (3D) flight path. We evaluate the analysis of different imaging methods performed with active laser detection as well as with passive imaging using advanced scenario analysis. In first experimental investigation, we recorded and analyzed image sequences of a MUAV quad-copter flying at low altitude in laboratory and in outdoor scenario. Our results show, that we are able to track the three dimensional flight path with high accuracy and we are able to give a reliable prediction of the MUAV flight behavior within the near future.
Conference Presentation
© (2019) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Martin Laurenzis, Martin Rebert, Emmanuel Bacher, and Stéphane Schertzer "Active and passive computational imaging for tracking and prediction of three-dimensional MUAV flight paths", Proc. SPIE 11160, Electro-Optical Remote Sensing XIII, 1116009 (10 October 2019); https://doi.org/10.1117/12.2532727
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