Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/144480
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dc.contributor.authorWang, John Chung-Hungen_US
dc.contributor.authorLow, Kin Huaten_US
dc.contributor.authorNg, Ee Mengen_US
dc.contributor.authorChan, E. Yang Jieen_US
dc.date.accessioned2020-11-06T06:12:58Z-
dc.date.available2020-11-06T06:12:58Z-
dc.date.issued2020-
dc.identifier.citationWang, J. C.-H., Low, K. H., Ng, E. M., & Chan, E. Y. J. (2020). Data analysis on track deviation of UAS operating under Visual Line of Sight (VLoS) condition. Proceedings of the AIAA Aviation 2020 Forum. doi:10.2514/6.2020-2899en_US
dc.identifier.isbn978-1-62410-598-2-
dc.identifier.urihttps://hdl.handle.net/10356/144480-
dc.description.abstractThe management of collision risk posed by recreational unmanned aerial systems (UAS) intruding into controlled airspace is becoming more critical with the surge in accessibility and popularity of these UAS. Risk mitigation actions that could be taken by the airport operators currently are limited by the lack of reliable UAS detection equipment, which limits their ability to track UAS positions over time and predict the collision risks posed by the UAS. While recent developments in airborne collision prevention of manned aircraft could utilize Markov Decision Process with state probabilities based on historical flight track records and processed using Bayesian Network, this method is not suitable for the off-nominal case of UAS intrusion into controlled airspace. Instead, the prediction of collision risk posed by non-cooperative recreational UAS have to rely on the assumption of worst-case intention, where the UAS aims for the aircraft operating within the aerodrome, and the Reich collision risk model to generate the probable distribution of future UAS positions. This paper documents a series of flight test to simulate such scenario with a UAS operating under visual line of sight condition while aiming for an imaginary three dimensional target in the air. The data was analyzed for the deviation in UAS positions at fixed time interval in the (horizontal) longitudinal and lateral direction, as well as the deviation in altitude. A comparison between the observed deviation and a Monte-Carlo based UAS path prediction following the UAS flight dynamic model were also conducted.en_US
dc.language.isoenen_US
dc.rights© 2020 Nanyang Technological University Singapore. Published by the American Institute of Aeronautics and Astronautics, Inc., with permission.en_US
dc.subjectEngineering::Aeronautical engineering::Aviationen_US
dc.titleData analysis on track deviation of UAS operating under Visual Line of Sight (VLoS) conditionen_US
dc.typeConference Paperen
dc.contributor.schoolSchool of Mechanical and Aerospace Engineeringen_US
dc.contributor.conferenceAIAA Aviation 2020 Forumen_US
dc.contributor.researchAir Traffic Management Research Instituteen_US
dc.identifier.doi10.2514/6.2020-2899-
dc.description.versionAccepted versionen_US
dc.subject.keywordsData Analysisen_US
dc.subject.keywordsAir Traffic Managementen_US
dc.description.acknowledgementThe authors would like to thank Air Traffic Management Research Institute for funding this research under the Urban Aerial Transport Traffic Management and Systems (UAT-TM&S) Project. The authors would also like to thank Mr. Shi Kun Tan for his assistant with flight data collection.en_US
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