OUSD (R&E) CRITICAL TECHNOLOGY AREA(S): Space Technology
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OBJECTIVE: Develop methods for reducing the latency in space object maneuver detection, utilizing existing sensor phenomenologies, cadences, and data types, with the objective of identifying and characterizing the maneuver with as few observations and as short of time as possible.
DESCRIPTION: The ability to detect space object maneuvers is fundamental in enabling space domain awareness and space traffic management. When a space object maneuvers, deviations from its previous track can be sufficiently large to prohibit association of the observed object to the track. The result is an uncorrelated track (UCT), a trackable object whose origin has not yet been established. Only upon reconciliation of the UCT to a previously known object's track can the association be made so that a full state history of the track is available. This process, known colloquially as UCT resolution, typically involves the backwards and forward propagation of states to identify possible candidate maneuver times, and is often done well after the maneuver has been performed. This time lag can result in critical information about maneuvering satellites to be delayed in sharing with analysts who monitor the space object population. While the optimal solution involves observing all maneuvering satellites persistently, such a solution is not feasible. The best case is therefore for analysts to detect, characterize, and identify satellite maneuvers as soon as new observation data is collected.
Solutions are sought that enable space object maneuver detection with limited latency once new observational data has been acquired. This will aid in maintaining persistent awareness of on-orbit objects. The problem is further compounded by the various orbital regimes in which important space assets reside, and the various sensor phenomenologies that dominate that regime. Solutions that bridge various orbital regimes, allowing for a comprehensive all-space solution are preferred to regime-specific solutions.
PHASE I: Develop solution methodology. Conduct analysis of alternatives, propose solution, and develop algorithm. Algorithm should be implemented in prototype simulations against synthesized or real data to demonstrate potential for success. Assess computing requirements necessary for Phase II effort.
PHASE II: Fully develop and implement solution methodology as prototype software. Methodology should be tested against real-world data across multiple orbital regimes. Quantify performance across multiple sensor types including variations to noise and sensing cadence. Compare timeliness of detection and characterization performance to legacy methods.
PHASE III DUAL USE APPLICATIONS: Phase III efforts may include integration of solution into operational test environments for evaluation with real-time data feeds, and transition to operational users. Military applications include more timely and accurate conjunction assessment and threat awareness. Expected TRL at Phase III entry is 5.
- B. Jia et al., "Space object tracking and maneuver detection via interacting multiple model cubature Kalman filters," 2015 IEEE Aerospace Conference, Big Sky, MT, USA, 2015, pp. 1-8, doi: 10.1109/AERO.2015.7119076.;
- N. Singh, J. T. Horwood, and A. B. Poore, “Space object maneuver detection via a joint optimal control and multiple hypothesis tracking approach,” in Proceedings of the 22nd AAS/AIAA Space Flight Mechanics Meeting, Charleston, SC, January 2012 (Paper AAS-12-159);
- Pastor, A., Escribano, G., Sanjurjo-Rivo, M. et al. Satellite maneuver detection and estimation with optical survey observations. J Astronaut Sci 69, 879–917 (2022). https://doi.org/10.1007/s40295-022-00311-5;
KEYWORDS: space domain awareness; space situational awareness; space traffic management; maneuver detection