Characterization and Typing of Hard-to-Acquire Targets using Advanced Machine Learning Methods on WFOV Staring Data
ID: SF243-D003Type: Phase II
Overview

Topic

Characterization and Typing of Hard-to-Acquire Targets using Advanced Machine Learning Methods on WFOV Staring Data

Agency

Agency: DODBranch: USAF

Program

Type: SBIRPhase: Phase II

Topic Link

https://www.dodsbirsttr.mil/topics-app/

Additional Information

https://www.dodsbirsttr.mil/topics-app/
Timeline
    Description

    The Department of Defense, specifically the United States Air Force, is seeking proposals for the Small Business Innovation Research (SBIR) program focused on the development of advanced machine learning algorithms for the characterization and typing of hard-to-acquire targets using wide field of view (WFOV) staring data. The objective is to create a prototype software algorithm capable of detecting, identifying, and characterizing air- and space-based targets from uncued surveillance data, addressing challenges posed by the increasing complexity of satellite constellations, particularly in light of foreign developments. This initiative is crucial for enhancing space domain awareness and ensuring effective surveillance capabilities, with a focus on transitioning the developed technology into a commercial product for both government and commercial applications. Interested parties must submit their proposals by October 23, 2024, with further details available on the official SBIR website.

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