SBIR/STTR Research Award

Joint Air Strike Planner

Award identifier f4c770719a6c77c02cf917c328929aa4032ee6c317ef97ade4cca5a946cdcd35Awarding agency Department of Defense · Air Force

Award amount

$49,890

Program and phase

SBIR · Phase I

Award year

2021

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Award details

Awarding agency
Department of Defense
Branch
Air Force
Recipient company
SYSTEMS ENGINEERING INC
Proposal award date
2021-02-18
Contract end date
2021-05-19
UEI
MMHGLU3W7C61
Solicitation number
X20.3
Topic code
AF203-CSO1

Research abstract

Planning air combat missions requires the cooperation and coordination of five separate divisions within the Air Operations Center (AOC). These divisions work together to create an Air Tasking Order (ATO) from semi-manual human inputs. As the battlespace becomes more congested with autonomous vehicles and near-peer rivals, emerge with effective air defense systems, planning the most efficient and effective ATOs and their associated strike paths becomes exponentially more complicated. Despite being cognitively burdensome, no Artificial Intelligence (AI)/Machine learning (ML) tool is currently available to aid in this process. As a result, human planners use planning systems and C2 aids initially developed in the 1990s, which are augmented only by Microsoft Office. The mispairing of resources and technology results in the following systemic deficiencies in the air planning process:   Long Planning Cycles. Currently, ATOs cover 24 hours, but the planning cycle takes up to 72 hours to incorporate intelligence updates, especially outcomes of previous strikes.   Inability to quickly adjust Air Tasking Orders for unexpected weather, equipment failure, and enemy maneuvers, resulting in un-serviced targets and increased risk to aircrews. Inefficient Aircraft Routing and Support Placement. Humans cannot assign targets across a battlespace optimally. Inefficient striker routing and tanker/airborne command and control (C2) placement results in prolonged enemy engagement and higher risk to support assets.   To address these issues - to maximize the current effectiveness of US Air Power and to help ensure victory in any future war - Systems Engineering, Inc. (SEI) and Mid-Atlantic Defense Solutions (MADS) will develop the Joint Air Strike Planner (JASP), an AI/ML air combat planning system. Our solution leverages Command: Modern Operation (CMO), a commercial video game, and a military simulator. We will integrate CMO with custom machine learning and artificial intelligence software to autonomously find the most effective and efficient strike asset allocation and their respective strike routes. JASP will update the ATO based on the latest known enemy position, available resources, rules of engagement, and weather. We are thereby maximizing an air campaign’s lethality while minimizing civilian and military casualties.

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

17 SBIR/STTR records share this UEI (1983–2024). Reported award amounts total $3,442,797. Reported amounts are not federal obligations.

Phases: Phase I, Phase II

Agencies: Department of Defense, Department of Homeland Security, National Aeronautics and Space Administration

Agency intelligence

Department of Defense

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