Resident Space Object Tracking for Space Situational Awareness

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dc.contributor.advisorLee, Regina S. K.
dc.contributor.authorKunalakantha, Perushan
dc.date.accessioned2024-11-07T11:21:18Z
dc.date.available2024-11-07T11:21:18Z
dc.date.copyright2024-08-02
dc.date.issued2024-11-07
dc.date.updated2024-11-07T11:21:17Z
dc.degree.disciplineEarth & Space Science
dc.degree.levelMaster's
dc.degree.nameMSc - Master of Science
dc.description.abstractThis research presents several contributions aimed at improving the current state of Space Situational Awareness (SSA) using optical imagery. The first component involved the development of an image capture algorithm which was successfully used to acquire over 90000 optical images from the stratosphere, with hundreds of visually verified Resident Space Objects (RSOs). The second component involved the development of a novel RSO tracking algorithm which was able to detect 87% of the RSOs in an 878-image dataset at least once. The third component proposed an automated annotation framework and corresponding four-tool annotation suite to develop a 500-image dataset to train and test another RSO tracking algorithm. The final component involved the demonstration of a dual-purpose payload, performing RSO detection alongside an existing Attitude Determination (AD) algorithm which detected 11 unique RSOs in real-time during another stratospheric balloon mission.
dc.identifier.urihttps://hdl.handle.net/10315/42528
dc.languageen
dc.rightsAuthor owns copyright, except where explicitly noted. Please contact the author directly with licensing requests.
dc.subjectAerospace engineering
dc.subjectAtmospheric sciences
dc.subjectAstronomy
dc.subject.keywordsSpace
dc.subject.keywordsResident space objects
dc.subject.keywordsMachine learning
dc.subject.keywordsICP
dc.subject.keywordsAlgorithm
dc.subject.keywordsSpace objects
dc.subject.keywordsObject tracking
dc.subject.keywordsRSO
dc.subject.keywordsRSO tracking
dc.subject.keywordsRSO data
dc.subject.keywordsData labelling
dc.subject.keywordsSpace mission
dc.titleResident Space Object Tracking for Space Situational Awareness
dc.typeElectronic Thesis or Dissertation

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