Date of Award
2022
Document Type
Thesis
Degree Name
Master of Science in Engineering (MSE)
Department
Mechanical and Aerospace Engineering
Committee Chair
Naga Venkat Adurthi
Committee Member
Farbod Fahimi
Committee Member
Robert A. Frederick Jr.
Subject(s)
Space debris--Tracking, Artificial satellites--Tracking
Abstract
There are thousands of objects in space with only a few sensors. Also when multiple objects are observed by a sensor, there is often an ambiguity of which measurement belongs to which object. This research intends to find a solution to this data association problem by developing a joint data association and orbit determination approach to adaptively assist the data association problem in tracking all the objects as accurately as possible. The solution studied throughout this thesis is the Multiple Hypothesis Tracker, a structure that comprises all the observations combinations. Then, a gating system of initial orbit determination, orbit determination and Kallman Filters will be used to prune unnecessary branches. Two simulations of 10 and 100 respectively were made. In both cases, the method is able to detect and track all of them. Following these good results, more work should be made toward this direction of using the Multiple Hypothesis Tracker for space object detection.
Recommended Citation
Richard, Thibault, "Adaptive data association using multiple hypothesis tracker for space object tracking" (2022). Theses. 397.
https://louis.uah.edu/uah-theses/397