Is this project an undergraduate, graduate, or faculty project?
Undergraduate
Project Type
group
Campus
Daytona Beach
Authors' Class Standing
David Stoev, Junior Oshani Jayawardane, Junior Kaitlyn Cavanaugh, Junior Kristiyan Stefanov, Junior Andrew Murphy, Senior
Lead Presenter's Name
David Stoev
Lead Presenter's College
DB College of Engineering
Faculty Mentor Name
Dr. Sirani Mututhanthrige Perera
Abstract
The Circular Restricted Three-Body Problem (CR3BP) is renowned for its intricate and chaotic dynamics, leaving it without a closed-form solution. In this poster, we introduce an innovative approach to determine spacecraft trajectories within the CR3BP framework using matrix factorization techniques. We formulate a matrix equation where the right-hand side vector is constructed from the spacecraft's position and velocity data, while the coefficient matrix is derived from the spacecraft's temporal data. Subsequently, we apply several matrix decomposition techniques, including modified Gram-Schmidt, the Householder technique, and Givens Rotation, to analyze the coefficient matrix and derive the spacecraft trajectories. Finally, we evaluate the execution time and floating-point operations(FLOPS), alongside the numerical stability of each method, to obtain a quantitative comparison of the proposed techniques.
Did this research project receive funding support (Spark, SURF, Research Abroad, Student Internal Grants, Collaborative, Climbing, or Ignite Grants) from the Office of Undergraduate Research?
No
Included in
Advancements in Spacecraft Trajectory Generation through Matrix Decomposition Techniques
The Circular Restricted Three-Body Problem (CR3BP) is renowned for its intricate and chaotic dynamics, leaving it without a closed-form solution. In this poster, we introduce an innovative approach to determine spacecraft trajectories within the CR3BP framework using matrix factorization techniques. We formulate a matrix equation where the right-hand side vector is constructed from the spacecraft's position and velocity data, while the coefficient matrix is derived from the spacecraft's temporal data. Subsequently, we apply several matrix decomposition techniques, including modified Gram-Schmidt, the Householder technique, and Givens Rotation, to analyze the coefficient matrix and derive the spacecraft trajectories. Finally, we evaluate the execution time and floating-point operations(FLOPS), alongside the numerical stability of each method, to obtain a quantitative comparison of the proposed techniques.