High Efficiency Angles-Only Space-Based Approaches for Geosynchronous Orbit Catalog Maintenance With Sparse Information
Date of Award:
Doctor of Philosophy (PhD)
Mechanical and Aerospace Engineering
The thesis of this dissertation proposes a novel filter algorithm to improve tracking and catalog maintenance of uncooperative satellites and other Resident Space Objects (RSOs) in Geosynchronous Equatorial Orbit (GEO). Tracking can be supported by space-based tracking from observer satellites (OBSs). Practical limitations can lead to long time gaps between measurement updates when tracking RSOs from an OBS, which may induce a loss of fidelity or divergence of the estimation algorithm. The Extended Kalman filter (EKF) is commonly used for tracking RSOs but it diverges as a consequence of nonlinearity in the dynamics and nonlinearity in the optical measurements from OBSs. Both nonlinear- ities cause the underlying probability density (PDF) of the state vector to deviate from a Gaussian distribution, leading to divergence after measurement update. The Unscented Kalman filter (UKF) and the Gaussian Mixture Model filter (GMM) were proposed to solve the divergence problem in the EKF. A hybrid algorithm, the Hybrid Kalman-particle filter (HKF), was developed and likewise assessed to improve on the EKF methodology by com- bining with particle filtering techniques. Lastly, this work presents a novel filter algorithm, the Extended Step-Back Kalman filter (ESBKF), in which the measurement update is ap- plied at a time in the past when the distribution of the RSO in state-space is approximately Gaussian. The filter statistics are then propagated forward to the present, and the nonlinear effects of the dynamics are dramatically reduced, thereby avoiding divergence longer.
Tonc, Louis M., "High Efficiency Angles-Only Space-Based Approaches for Geosynchronous Orbit Catalog Maintenance With Sparse Information" (2023). All Graduate Theses and Dissertations. 8776.
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