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Advanced Hierarchical Temporal Memory (HTM) and AI/ML Algorithm Study

Award Information
Agency: Department of Defense
Branch: Missile Defense Agency
Contract: HQ0860-21-C-7121
Agency Tracking Number: B2-3029
Amount: $1,495,675.00
Phase: Phase II
Program: SBIR
Solicitation Topic Code: MDA19-004
Solicitation Number: 19.2
Solicitation Year: 2019
Award Year: 2021
Award Start Date (Proposal Award Date): 2020-12-21
Award End Date (Contract End Date): 2022-12-20
Small Business Information
251 18th Street S Suite 705
Arlington, VA 22202-3541
United States
DUNS: 053885604
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Jeffery Philson
 (203) 601-8329
Business Contact
Phone: (301) 576-2303
Research Institution

An evolving set of missile threats will challenge Integrated Air and Missile Defense (IAMD) in the future. Advanced long-range radar is one component of a system to counter this threat, yet such powerful radars can also inadvertently detect and track a number of non-threat objects and signals in the environment. In Phase 1, TSC reviewed advanced methods in Artificial Intelligence (AI) and Machine Learning (ML), developed prototype AI/ML algorithms to mitigate the impact of such non-threat objects and signals on Ballistic Missile Defense (BMD) radars, and demonstrated the feasibility of this approach on a surrogate problem. In Phase II, TSC will expand the scope of work including exploring a broader set of AI/ML techniques, modifying the algorithms for application to specific operational systems, and validating the overall approach on measured and higher-fidelity simulated datasets. Approved for Public Release | 20-MDA-10643 (3 Dec 20)

* Information listed above is at the time of submission. *

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