SBIR/STTR Research Award

LG AI-based Battle Management (BM) for Integrated Air and Missile Defense (IAMD)

Award identifier e73088698857d2c2d38156c1c1c5c1781e297c3a4cc0a283c38f710cc240b710Awarding agency Department of Defense · Missile Defense Agency

Award amount

$1,494,965

Program and phase

SBIR · Phase II

Award year

2021

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Award details

Awarding agency
Department of Defense
Branch
Missile Defense Agency
Recipient company
STILMAN ADVANCED STRATEGIES, LLC
Proposal award date
2021-02-04
Contract end date
2023-02-03
UEI
KG5YKVBV5UW9
Solicitation number
19.2
Topic code
MDA19-005

Research abstract

Manual multi-domain kill chain planning for Integrated Air and Missile Defense (IAMD) is labor intensive and too slow to effectively respond to time critical targets. STILMAN has developed an Artificial Intelligence (AI)-based planning and supervisory decision aid algorithms and software for resource allocations (sensors and weapons) across multiple domains in real-time. This AI approach is based on Linguistic Geometry (LG), a break-through in constructive game-theory solutions originally developed by Dr. Boris Stilman and further refined by the STILMAN company. This LG AI capability is ideally suited to quickly solve extraordinarily complex IAMD resource planning and allocation problems. As the frequency and size of raids escalates, the urgency of the response and the complexity of resource allocation decisions increases. Within a multi-domain (near-Earth Space, Air, Land, and Sea) battlespace, exacerbated by presence of both conventional weapons and ballistic missiles/interceptors, this complexity can quickly overwhelm the human commander’s ability to successfully plan and respond. STILMAN’s AI-based algorithms and software provide dynamic kill chain planning and preview capability enabling the commander to deal with such complexity. The LG AI-based analysis is fast, flexible, scalable, and explainable – and it applies to multi-domain and multi-tier sensor and weapon platforms. Dynamic, reactive resource allocation recommendations are displayed via 2D or 3D animations that provide the human commander with an on-the-loop visualization that prioritizes resource allocations in faster than real-time. This is particularly advantageous for servicing pop-up targets that suddenly appear outside of the pre-planned mission profile. Approved for Public Release | 20-MDA-10643 (3 Dec 20)

Technology keywords

Not reported

Other awards by this recipient

Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.

Awards with the same topic code

Verified by an exact topic code match. This is not a text-similarity match.

Research funding history

21 SBIR/STTR records share this UEI (2002–2025). Reported award amounts total $14,833,546. Reported amounts are not federal obligations.

Phases: Phase I, Phase II

Agencies: Department of Defense

Agency intelligence

Department of Defense

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