Optical Orbit Tracking and Estimation

<p>Angles-only initial orbit determination methods are currently limited in their use as they require some prior knowledge of where the observed object will be and when it will be there. This research aims to produce a viable method to automate this process so that objects whose trajectories are not saved in a user’s catalog can be observed. A method is devised using a novel approach to satellite recognition in an image. This method is used in addition to Astrometry to determine the right ascension and declination of the object. This information is then used to either obtain the initial conditions needed for a state estimator or is utilized by a Kalman Filter to correct any resulting error. In addition, an extra goal is set to create a modular process so that any stage of the end-to-end process can be changed to suit a user’s individual needs while still being able to perform the task for which it was assigned. Tests with varying times between measurements were first run to determine if a discrete-time Kalman Filter is a viable method to correct the error created by the state estimator, where coordinates were fed directly into the filter with no images. These tests showed that the filter succeeded in its goal of adjusting the projections made by the mathematical representation of the satellite’s trajectory based on measured data. After this, tests were done on images that were acquired in a manner similar to how the filter would have acquired them to test the entire end-to-end process. This test demonstrated that the end-to-end process worked as intended, with the Kalman Filter keeping the error well within the image. This means that if the projection is in the middle of the image, the centroid of the satellite streak will be in the middle well. A final test was conducted to implement the Kalman Filter on a telescope system while utilizing a different image processing technique. This test demonstrated that the Kalman Filter worked as intended in real time.</p>

Name thesis:degree_name

Master of Science in Aerospace Engineering

Level thesis:degree_level

Thesis - Open Access

Discipline thesis:degree_discipline

Aerospace Engineering

Year

2023

Author dc:creator

• Gillette, Matthew

• Kalman Filtering
• Orbit Determination
• Satellite Trajectory
• Discrete Time
• Navigation, Guidance, Control and Dynamics

Repository record dc:identifier

https://commons.erau.edu/edt/751

OAI identifier oai:identifier

oai:commons.erau.edu:edt-1760