Print Email Facebook Twitter U-space field trials results for drone discrimination with a staring radar Part of: 3rd International Specialist Meeting "Electromagnetic Waves and Wind Turbines 2018"· list the conference papers Title U-space field trials results for drone discrimination with a staring radar Author Jahangir, Mohammed (Aveillant, University of Birmingham) Date 2018-12-07 Abstract Non-cooperative surveillance of drones is an important consideration in the EU SESAR vision for the provision of U-SPACE services. Aveillant Gamekeeper multiple staring radar utilises extended dwell to be able to detect small drones at the range of several kilometres. However, target discrimination is necessary with such surveillance system as the increased detection sensitivity against low RCS targets extenuates the problem of false reports of targets such as birds and surface objects such as vehicles etc. Machine learning classifiers are used to remove confuser targets such as birds to provide real-time tracks of drones. Field trials from live drone flights against a number of test scenarios for U-Space are used to train and test a decision tree classifier working on both trajectory and micro-doppler features. Results show that a high level of classifier accuracy is achieved across a range of flight profiles for a rotary wing drone. To reference this document use: http://resolver.tudelft.nl/uuid:4a3f4582-b5ea-41fc-974c-5193264f59e9 Part of collection Conference proceedings Document type conference paper Rights (c) the author Files PDF A13.pdf 3.66 MB Close viewer /islandora/object/uuid:4a3f4582-b5ea-41fc-974c-5193264f59e9/datastream/OBJ/view