Hybrid Gaussian Mixture Splitting Techniques for Uncertainty Propagation in Nonlinear Dynamics

No AccessEngineering NotesHybrid Gaussian Mixture Splitting Techniques for Uncertainty Propagation in Nonlinear DynamicsPan Sun, Camilla Colombo, Mirko Trisolini and Shuang LiPan Sun https://orcid.org/0000-0001-6182-4503Nanjing University of Aeronautics and Astronautics, 210016 Nanjing, People’s Republic of China*Ph.D. Candidate, Advanced Space Technology Laboratory, and College of Astronautics; .Search for more papers by this author, Camilla Colombo https://orcid.org/0000-0001-9636-9360Polytechnic University of Milan, 20156 Milan, Italy†Associate Professor, Department of Aerospace Science and Technology; .Search for more papers by this author, Mirko Trisolini https://orcid.org/0000-0001-9552-3565Polytechnic University of Milan, 20156 Milan, Italy‡Postdoc Research Fellow, Department of Aerospace Science and Technology; .Search for more papers by this author and Shuang Li https://orcid.org/0000-0001-9142-5036Nanjing University of Aeronautics and Astronautics, 210016 Nanjing, People’s Republic of China§Professor, Advanced Space Technology Laboratory, and College of Astronautics; .Search for more papers by this authorPublished Online:27 Nov 2022https://doi.org/10.2514/1.G006696SectionsRead Now ToolsAdd to favoritesDownload citationTrack citations ShareShare onFacebookTwitterLinked InRedditEmail About References [1] Psiaki M. 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V. and Getino J., “Orbital Evolution of High-Altitude Balloon Satellites,” Astronomy and Astrophysics, Vol. 318, Feb. 1997, pp. 308–314. Google Scholar Previous article Next article FiguresReferencesRelatedDetailsCited byAdaptive Gaussian Mixture Model for Uncertainty Propagation Using Virtual Sample Generation27 February 2023 | Applied Sciences, Vol. 13, No. 5 What's Popular Volume 46, Number 4April 2023 CrossmarkInformationCopyright © 2022 by the authors. Published by the American Institute of Aeronautics and Astronautics, Inc., with permission. All requests for copying and permission to reprint should be submitted to CCC at www.copyright.com; employ the eISSN 1533-3884 to initiate your request. See also AIAA Rights and Permissions www.aiaa.org/randp. TopicsAerospace SciencesArtificial IntelligenceAstrodynamicsAstronauticsComputing, Information, and CommunicationData ScienceEntropyMachine LearningOrbital ManeuversSpace OrbitStructural Design and DevelopmentStructural Kinematics and DynamicsStructures, Design and TestThermodynamic PropertiesThermodynamicsThermophysics and Heat Transfer KeywordsStructural Kinematics and DynamicsEntropyGaussian Mixture ModelsMedium Earth OrbitOrbital MechanicsPlanetsProbability Density FunctionsOrbit DeterminationSolar RadiationHydrodynamicsAcknowledgmentsThis research work has received funding from the National Natural Science Foundation of China (Grant Nos. 11972182 and 11672126), Qing Lan Project, China Scholarship Council (CSC No. 202006830123), and the 2020 Postgraduate Research Practice Innovation Program of Jiangsu Province (Grant No. KYCX20_0222). C. Colombo and M. Trisolini acknowledge the COMPASS project, which has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation program (Grant Agreement No. 679086—COMPASS). Pan Sun acknowledges the anonymous reviewers for the constructive comments for improving the paper.PDF Received19 January 2022Accepted9 October 2022Published online27 November 2022