The Center for Space Research and Assurance at the U.S. Air Force Institute of Technology investigates short-term tactical spacecraft missions that require frequent maneuvers. An important part of this research is developing methods of performing orbit determination on noncooperative spacecraft that maneuver often at unknown times with unknown thrusts. When a spacecraft performs long-duration thrusts in view of radars, traditional orbit determination, and batch least-squares routines are ineffective methods of fitting the orbit. Adaptive variable-state dimension filters allow for accurate orbit and thrust acceleration estimation during long-duration maneuvers. This work develops and evaluates routines that use both an extended and unscented augmented state Kalman filter along with interacting multiple models to estimate maneuvers. Several methods are evaluated to determine the start and conclusion of continuous maneuvers, and a multiple-model approach is introduced to determine the conclusion of low-thrust continuous maneuvers. Simulation results show that the variable-state dimension interacting multiple model is best at estimating orbits across all thrust levels, whereas a process noise single-model variable-state dimension filter is best when properly tuned for a general thrust magnitude.
Orbit Estimation of a Continuously Thrusting Spacecraft Using Variable Dimension Filters
Journal of Guidance, Control, and Dynamics ; 38 , 12 ; 2407-2420
2015-12-01
Conference paper , Article (Journal)
Electronic Resource
English
Orbit Estimation of a Continuously Thrusting Spacecraft Using Variable Dimension Filters
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