A Dynamic Sensor Tasking Strategy for Tracking Maneuvering Spacecraft using Multiple Models
Document Type
Conference Proceeding
Publication Date
1-1-2016
Abstract
Space domain awareness demands accurate real-time state knowledge of orbiting objects for peaceful space operations. Since there are a far greater amount of satellites than there are observing sensors, it is very important to task sensors effectively while also adapting for potential unknown orbit changes. This research effort outlines an information based tasking strategy to track non-cooperative satellites using ground-based radars. Further-more, unknown maneuvers are estimated by using a covariance inflation filter-through approach within an Interacting Multiple Model framework for both continuous and instantaneous maneuvers. The simulations presented show the effectiveness of a real-time, adaptive, multiple-model orbit estimation routine which dynamically tasks radars based on the Shannon information of the state estimate. Several information threshold strategies are presented using realistic ground configurations to highlight a new way to prioritize sensor resources to collect on a non-cooperative maneuvering spacecraft. The results confirm that adaptive information based tasking is successful in maintaining accurate state knowledge of maneuvering spacecraft.
Source Publication
AIAA Guidance, Navigation, and Control Conference
Recommended Citation
Goff, G. M., Black, J. T., Beck, J. A., & Hess, J. A. (2016). A Dynamic Sensor Tasking Strategy for Tracking Maneuvering Spacecraft using Multiple Models. AIAA Guidance, Navigation, and Control Conference, Session: Novel Navigation, Estimation and Tracking II. https://doi.org/10.2514/6.2016-1859
Comments
This conference paper is available through subscription or purchase from the publisher, AIAA, using the DOI link below.
Conference session: Novel Navigation, Estimation and Tracking II
Author note: Joshua Hess was an AFIT PhD candidate at the time of this conference. (AFIT-ENY-DS-16-S-061, September 2016)