Hybrid Intelligent Algorithms Enhanced Optimization of Approach Trajectories for Low-Altitude Flight Targets in Dynamic Thunderstorm Scenarios

Hybrid Intelligent Algorithms Enhanced Optimization of Approach Trajectories for Low-Altitude Flight Targets in Dynamic Thunderstorm Scenarios | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Hybrid Intelligent Algorithms Enhanced Optimization of Approach Trajectories for Low-Altitude Flight Targets in Dynamic Thunderstorm Scenarios Li Lu, Keyun Ye, Kuan Wang, Jianan Zhang, Tianhang Wang, Ruixi Mao, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9156965/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 8 You are reading this latest preprint version Abstract The instrument approach is the segment most severely affected by convective weather during the entire flight. This study introduces an integrated method for safe four-dimensional (4D) approach-trajectory optimization in dynamic thunderstorm scenarios. The process begins by extracting structural features of thunderstorm data through clustering and Monte Carlo-based correlation analysis, followed by short-term movement prediction using weighted interpolation. Based on the above results, a hybrid RRT-APF algorithm generates a dynamic thunderstorm-avoidance trajectory. To address local distortions in the plan view, the method applies a round mean filter to remove unstable waypoints while preserving key spatiotemporal characteristics of the route. Ultimately, a flight-procedure validation system assesses the overall research performance. The results demonstrate a thunderstorm-movement prediction accuracy of 93.7%, an optimized descent gradient of 3.73% during the final approach, and the hybrid RRT-APF algorithm cost of 0.2795, in compliance with the instrument approach design standards. Collectively, the research method yields smooth and reliable 4D trajectories, providing an effective basis for safe approach operations in convective weather, as well as future research on multi-aircraft conflict resolution under thunderstorm conditions. Physical sciences/Engineering Physical sciences/Mathematics and computing Earth and environmental sciences/Natural hazards Intelligent air traffic management Flight trajectory optimization Thunderstorm scenarios prediction Round mean filter Optimized trajectory Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 13 May, 2026 Reviewers agreed at journal 13 May, 2026 Reviewers agreed at journal 07 Apr, 2026 Reviewers invited by journal 03 Apr, 2026 Editor invited by journal 23 Mar, 2026 Editor assigned by journal 19 Mar, 2026 Submission checks completed at journal 19 Mar, 2026 First submitted to journal 18 Mar, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9156965","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":619217896,"identity":"9f201abd-cada-4b76-bb16-a2cac0781e17","order_by":0,"name":"Li 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