You are here

Space Object Energy Parameter and State Inference To Support Object Detection, Tracking, Identification and Classification


TECHNOLOGY AREA(S): Information Systems

The technology within this topic is restricted under the International Traffic in Arms Regulation (ITAR), 22 CFR Parts 120-130, which controls the export and import of defense-related material and services, including export of sensitive technical data, or the Export Administration Regulation (EAR), 15 CFR Parts 730-774, which controls dual use items. Offerors must disclose any proposed use of foreign nationals (FNs), their country(ies) of origin, the type of visa or work permit possessed, and the statement of work (SOW) tasks intended for accomplishment by the FN(s) in accordance with section 5.4.c.(8) of the solicitation and within the AF Component-specific instructions. Offerors are advised foreign nationals proposed to perform on this topic may be restricted due to the technical data under US Export Control Laws. Please direct questions to the AF SBIR/STTR Contracting Officer, Ms. Gail Nyikon,

OBJECTIVE: Focusing specifically on inferring space object energy parameters and states that could be used to classify the type of object.

DESCRIPTION: The fundamental values that could be used to understand any given space object are in terms of the object’s energy and momentum states. In some instances, conservation of energy and momentum principles can be used to easily bound the physical behavior of an object. The simplest energy to infer on a space object is perhaps its orbital energy, which if not maneuvering, is fairly constant over short time periods. Furthermore, in reality there are other energy states that one could attempt to infer, such as rotational energy states, and those that further depend on the interaction of the space environment with the object, such as reflected energy, absorbed energy, and thermally radiated energy. These last types of energy could be represented as vectors as well. All of these types of energy, combined, can reveal the type of object that is being observed and can bound its possible states of behavior. One could envision developing a database where space objects are tracked based upon these various types of energy and momentum parameters. Changes in energy and momentum states should be simpler to infer and could serve as a mechanism for indications and warning of hazards or threats. The fundamental requirement for this activity to be successful is to explore methods that can be used to track, infer, and quantify the ambiguity in these various types of energy (i.e., orbital, rotational, reflected, absorbed, and radiated). Rocket bodies, for instance, may have specific energy and momentum “signatures” or “fingerprints” that are unique. These energy and momentum states will be highly dependent on the object’s physical characteristics (e.g., size, shape, materials, orbit, orientation, etc.) but perhaps even functional characteristics (e.g., mission, capabilities, etc.). The manner in which we collect data also has a contribution to the inferred energy and momentum states, and thus sensor tasking methods to contribute to this inference should also be pursued and investigated.

PHASE I: Identify the possible sensors and combinations that could be employed for space object energy state inference and quantification, and derive the mathematical relationships between those sensors and space object parameters of interest to infer. Design and develop estimation techniques to infer all of the energy states of interest (i.e., orbital, rotational, reflected, absorbed, and radiated).

PHASE II: Develop/update the technology based on Phase I to provide a prototype demonstration of the technology in a realistic environment using actual sensor data, with errors and biases as well as realistic processing speeds in complex scenarios. This may fit in supporting various Air Force Research Laboratory R&D programs and flight experiments.

PHASE III DUAL USE APPLICATIONS: Integrate algorithm enhancement technology into a Major Defense Acquisition Program (MDAP) programs of record, such as JSpOC Mission System (JMS). Partnership with traditional DoD prime contractors is encouraged to facilitate successful transition and integration into an operational environment.


    • DeMars, K., Hussein, I., Früh, C., Jah, M., Erwin, R., (2014). Multiple Object Space Surveillance Tracking Using Finite Set Statistics. AIAA Journal of Guidance, Control, and Dynamics, Accepted (12/3/2014).


    • J. Stauch, M. Jah, J. Baldwin, T. Kelecy, K. Hill, (2014). “Mutual Application of Joint Probabilistic Data Association, Filtering, and Smoothing Techniques for Robust Multiple Space Object Tracking,” Invited, AIAA/AAS Astrodynamics Specialist Conference, San Diego, CA, August, AIAA 2014-4365.


    • C. Früh, M. Jah, E.Valdez, T. Kelecy, P. Kervin, (2013). “Initial Taxonomy and Classification Scheme for Artificial Space Objects,” Proceedings of the 2010 AMOS Technical Conference, Maui, Hawaii


    • Linares, R., Jah, M. K., Crassidis, J. L., and Nebelecky, C., (2014). Space Object Shape Characterization and Tracking Using Light Curve and Angles Data. AIAA Journal of Guidance, Control, and Dynamics, Vol. 37, No. 1, pp. 13-25.


  • Wetterer, C., Linares, R., Crassidis, J., Kelecy, T., Ziebart, M., Jah, M., P. Cefola., (2014). Refining Space Object Radiation Pressure Modeling with Bidirectional Reflectance Distribution Functions, AIAA Journal of Guidance, Control, and Dynamics, Vol. 37, No. 1, pp. 185-196.

KEYWORDS: multi-sensor, space, tracking, fusion, algorithm, taxonomy, energy

  • TPOC-1: Dr. Patrick McNicholl
  • Phone: 505-853-6590
  • Email:
US Flag An Official Website of the United States Government