DOPE: Dynamic Orbit Propagation for RealisticUncertainty Characterization in Low Earth Orbit

DOPE: Dynamic Orbit Propagation for RealisticUncertainty Characterization in Low Earth Orbit | 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 Research Article DOPE: Dynamic Orbit Propagation for RealisticUncertainty Characterization in Low Earth Orbit Rachit Bhatia, Piyush Mehta This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8813421/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Covariance realism in low Earth orbit (LEO) operations is critical for ensuring space safety. Realism requires both precise and accurate characterization of the vehicle dynamics and environment. This study focuses on modeling the temporal auto-correlation (half-life) in atmospheric density and associated uncertainty (both due to density model and space weather drivers), in real-time operations. Atmospheric density being a major perturbing force in LEO significantly impacts precise orbit prediction and uncertainty quantification. Current orbit determination (OD) / orbit propagation (OP) tools neglect the temporal auto-correlation component in atmospheric density and assume density to be deterministic with associated uncertainty modeled as process noise. This research presents a novel technique, named the Dynamic Orbit Propagator and Estimator (DOPE), to incorporate uncertainty in the atmospheric density model within state propagation and capture the temporal auto-correlation dynamics as a first-order Gauss-Markov (FOGM) process. This enables a realistic representation of density half-life within the real-time OD/OP framework. In DOPE, the state vector incorporates density perturbations ($\delta\rho$), preserving the standard propagation architecture while maintaining computational efficiency and operational practicality. This work forms part of the next-generation atmospheric drag modeling framework under development through efforts supported by the Intelligence Advanced Research Projects Activity (IARPA) Space Debris Identification and Tracking (SINTRA) program and the Office of Space Commerce (OSC). The technique presented here is a critical component of this framework. Monte Carlo (MC) simulations validate that varying half-life values produce statistically consistent orbital deviations, enhancing realism in orbit prediction, conjunction assessment, and reliable tracking of Resident Space Objects (RSOs). Temporal auto-correlation Covariance realism Orbital mechanics Atmospheric physics Space safety Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted 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-8813421","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":588715455,"identity":"1983649e-880b-4538-908f-8a1cfdeb4c83","order_by":0,"name":"Rachit Bhatia","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABIklEQVRIie3Qv0vDQBTA8ScHl+VK1pOG5l+4IDQKRf+VK4FMaR26CBXMlC72PxD/BqfOFwLtEsiaMRIIDh38AVIhQi9Su3gNjoL3ncLBh/fyAHS6vxkGDsCZ/BJwBeSXhDcESZLuCWsnsCNwFO1fDxN3llTF4wbGrpHF4uP+3DJnAr3mdW2DMS+fFMRKfZfJxSZntx7E84VHaMpxdxQxJySr/qmCUAgwlWT4IDwQnQUiIC7f0ShkHKiPVetRc70jWQnx590NsbMCvQV1C6HfU3IPkk6YEJZz6Ab4i6BCSao+5T6dsLxkibVcEScvmn85cSKyxKqLUdOrjjeDwZhlw/JlfT296GW8Waxnm0aEng+eWl7hZ3IEVr231zZFp9Pp/k9bqtBfbjVBFi4AAAAASUVORK5CYII=","orcid":"","institution":"West Virginia University","correspondingAuthor":true,"prefix":"","firstName":"Rachit","middleName":"","lastName":"Bhatia","suffix":""},{"id":588715456,"identity":"f9dbc210-c48c-411e-9218-eda515f5cf7f","order_by":1,"name":"Piyush Mehta","email":"","orcid":"","institution":"West Virginia University","correspondingAuthor":false,"prefix":"","firstName":"Piyush","middleName":"","lastName":"Mehta","suffix":""}],"badges":[],"createdAt":"2026-02-07 07:54:25","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8813421/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8813421/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":102398401,"identity":"c73e5ae6-a02f-4eaf-b396-c9c71b69e6f4","added_by":"auto","created_at":"2026-02-11 10:22:29","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2172225,"visible":true,"origin":"","legend":"","description":"","filename":"DOPEDynamicOrbitPropagationforRealisticUncertaintyCharacterizationinLowEarthOrbitRachit.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8813421/v1_covered_7ffa0f1b-f40f-4e3a-ada5-9c58486255fa.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"DOPE: Dynamic Orbit Propagation for RealisticUncertainty Characterization in Low Earth Orbit","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Temporal auto-correlation, Covariance realism, Orbital mechanics, Atmospheric physics, Space safety","lastPublishedDoi":"10.21203/rs.3.rs-8813421/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8813421/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eCovariance realism in low Earth orbit (LEO) operations is critical for ensuring space safety. Realism requires both precise and accurate characterization of the vehicle dynamics and environment. This study focuses on modeling the temporal auto-correlation (half-life) in atmospheric density and associated uncertainty (both due to density model and space weather drivers), in real-time operations. Atmospheric density being a major perturbing force in LEO significantly impacts precise orbit prediction and uncertainty quantification. Current orbit determination (OD) / orbit propagation (OP) tools neglect the temporal auto-correlation component in atmospheric density and assume density to be deterministic with associated uncertainty modeled as process noise.\u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis research presents a novel technique, named the Dynamic Orbit Propagator and Estimator (DOPE), to incorporate uncertainty in the atmospheric density model within state propagation and capture the temporal auto-correlation dynamics as a first-order Gauss-Markov (FOGM) process. 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