Abstract
Tracking geosynchronous space objects from ground-based sensors is a complicated task due to the large number of objects and limited number of available sensors, which are further restricted in the times they are operational. To maintain an accurate catalog, it is essential to collect measurements efficiently to maximize use of the limited information available. Recent advances in multitarget filtering and information theory allow formulation of sensor allocation schemes in terms of information gain functionals computed from the multitarget state and hypothesized measurements. This work develops a tasking scheme designed to take the fullest advantage of limited observation opportunities by maximizing the information gain. Simulation results are presented in which a representative catalog of nearly 1000 geosynchronous objects are tracked using three sensors. The results demonstrate that the method is able to schedule observations of all objects successfully where other ad hoc methods fall short.
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