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dc.contributor.advisorChakravorty, Suman
dc.creatorMishra, Utkarsh Ranjan
dc.date.accessioned2023-09-18T17:20:43Z
dc.date.created2022-12
dc.date.issued2023-01-10
dc.date.submittedDecember 2022
dc.identifier.urihttps://hdl.handle.net/1969.1/198806
dc.description.abstractSafe and sustainable operations in Geocentric Orbit require the acquisition, tracking, and predictive use of a large amount of data pertaining to the existence, characterization, and orbital state of objects in Earth orbit. The acquisition involves initializing the pdf of the objects in a catalog. Tracking involves the recursive update of the multi-target pdf. Conjunction assessment is perhaps the most common use of such a space catalog. This dissertation addresses these three fundamental building blocks of Space Domain Awareness (SDA): initialization, multi target tracking, and conjunction assessment. Towards this, we establish a connection between Reid’s Hypothesis Oriented Multi Hypotheses Tracking (HOMHT) and the modern Random Finite Set (RFS)/Finite Set Statistics (FISST) based methods for Multi-Target Tracking. In particular, we examine the different hypotheses, derive the hypotheses update equations under the FISST recursions, and clearly show its relationship to the classical HOMHT hypotheses and hypothesis weight update formula, thereby establishing a connection between the methods. The analytically computed value of the Probability of Collision for long-term engagements between two space objects using traditional schemes, which only consider some time span around the time of closest approach, can sometimes be incorrect by orders of magnitude. Sampling-based methods are presented as a robust alternative to analytical schemes. To decrease the computational burden of simulating a large number of particles, a novel subset simulation-based MCMC scheme is introduced to compute in-orbit space-object collision probability. The collision probability is expressed as a product of larger conditional failure probabilities by introducing intermediate failure events. Well-chosen large (relative to collision probability) values of nested conditional failure probabilities can be estimated by means of simulating only a limited number of samples. The resulting efficiency and accuracy of the suggested scheme are demonstrated against independent benchmarks that use other techniques for calculating the probability of collision.
dc.format.mimetypeapplication/pdf
dc.language.isoen
dc.subjectMCMC
dc.subjectSubset Simulations
dc.subjectMarkov Chain Monte Carlo
dc.subjectMonte Carlo
dc.subjectMC
dc.subjectFISST
dc.subjectMulti-Target Tracking
dc.subjectMulti-Object Tracking
dc.subjectMOT
dc.subjectMTT
dc.subjectMulti Hypothesis Tracking
dc.subjectBayesian Filtering
dc.subjectKalman Filter
dc.subjectParticle Filter
dc.subjectParticle Gaussian Mixture Filter
dc.subjectClustering
dc.titleOn Selected Topics in Space Domain Awareness
dc.typeThesis
thesis.degree.departmentAerospace Engineering
thesis.degree.disciplineAerospace Engineering
thesis.degree.grantorTexas A&M University
thesis.degree.nameDoctor of Philosophy
thesis.degree.levelDoctoral
dc.contributor.committeeMemberBhattacharya, Raktim
dc.contributor.committeeMemberDeMars, Kyle
dc.contributor.committeeMemberKumar, Panganamala R
dc.type.materialtext
dc.date.updated2023-09-18T17:20:44Z
local.embargo.terms2024-12-01
local.embargo.lift2024-12-01
local.etdauthor.orcid0000-0003-2310-9853


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