Data-driven synthetic air data estimation system development for a fighter aircraft

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dc.contributor.authorKarali, Hasan
dc.contributor.authorUzun, Mevlut
dc.contributor.authorYuksek, Burak
dc.contributor.authorInalhan, Gokhan
dc.date.accessioned2023-07-10T15:07:40Z
dc.date.available2023-07-10T15:07:40Z
dc.date.issued2023-06-08
dc.description.abstractIn this paper, we propose an AI-based methodology for estimating angle-of-attack and angle-of-sideslip without the need for traditional vanes and pitot-static systems. Our approach involves developing a custom neural-network model to represent the input-output relationship between air data and measurements from various sensors such as inertial measurement units. To generate the training data required for the neural network, we use a 6-degrees-of-freedom F-16 simulator, which is further modified to simulate more realistic flight data. The training data covers the full flight envelope, allowing the neural network to generate accurate predictions in all feasible flight conditions. Our methodology achieves high-accuracy estimations of angle-of-attack and angle-of-sideslip, with mean absolute errors of 0.534 deg and 0.247 deg, respectively, during the test phase. The results demonstrate the potential of the proposed methodology to accurately estimate important flight parameters without the need for complex and costly instrumentation systems. The proposed methodology could have significant practical applications in the aviation industry, particularly in next-generation aircraft instrumentation and control. Future research could focus on further refining the neural-network model and exploring its application in other aircraft systems to improve safety and reduce costs.en_UK
dc.identifier.citationKarali H, Uzun M, Yuksek B, Inalhan G. (2023) Data-driven synthetic air data estimation system development for a fighter aircraft. In: 2023 AIAA Aviation and Aeronautics Forum and Exposition (AIAA AVIATION Forum), 12-16 June 2023, San Diego, USA. Paper number AIAA 2023-3439en_UK
dc.identifier.isbn978-1-62410-704-7
dc.identifier.urihttps://doi.org/10.2514/6.2023-3439
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/19949
dc.language.isoenen_UK
dc.publisherAIAAen_UK
dc.rightsAttribution-NonCommercial 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/*
dc.titleData-driven synthetic air data estimation system development for a fighter aircraften_UK
dc.typeConference paperen_UK

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