AI-Enabled Computed Vision Air-to-Air Refueling Performance Assessment and Automated Pilot Debrief System

STTR · Phase: Phase II · Topic DAF27TZ01-DV001 · Solicitation 27.TZ

Air-to-air refueling (AAR) is a critical Department of the Air Force and Department of the Navy capability enabling global mobility, long-range strike, combat airpower projection, and sustained aviation operations. However, aerial refueling remains one of the most technically demanding and safety-critical aviation tasks performed by aircrews. Successful execution requires precise aircraft positioning, coordinated control inputs, accurate closure rate management, continuous situational awareness, and effective crew coordination between tanker and receiver aircraft.Current aerial refueling training and post-flight assessment processes rely heavily on instructor observation, pilot self-assessment, manual video review, and subjective evaluation of performance. These approaches provide limited ability to quantitatively assess the thousands of individual performance variables that influence successful refueling operations. Existing methods do not provide pilots with objective, moment-by-moment feedback on aircraft positioning, closure rates, control inputs, deviations from desired procedures, or trends in individual performance over time.This topic seeks to develop, demonstrate, and transition an artificial intelligence (AI)-enabled computed vision capability that (post-flight) automatically analyzes aerial refueling operations and provides objective, data-driven pilot performance feedback. The desired capability will mature existing advances in autonomous aerial refueling analytics and apply them toward training, readiness, and safety improvement by transforming aerial refueling video and available aircraft performance data into actionable post-flight debrief products.The developed system shall provide an automated “hot wash” which analyzes aerial refueling events, identifies performance deviations, and generates intuitive visualizations that allow pilots and instructors to better understand execution quality and areas for improvement. The system shall reduce reliance on subjective recollection and manual review by providing objective measurements of aircraft performance throughout the refueling profile.The capability shall focus on analysis of tanker-mounted video data, such as KC-46 aerial refueling camera systems, while maintaining an architecture capable of expanding across additional tanker and receiver platforms. The vendor may pick (with Government concurrence) the first 3-5 receiver platforms to use in developing this system. Future applicability includes KC-135, C-17, all fighter receiver aircraft, naval aviation communities, autonomous aerial refueling systems, and other aviation training environments requiring advanced performance analytics.The desired solution shall leverage artificial intelligence, machine learning, computer vision, and advanced human-machine interfaces to provide capabilities including:• Automated detection and tracking of tanker (boom and hose) and receiver aircraft during aerial refueling operations.• Measurement of relative aircraft position, movement, velocity, and alignment throughout the refueling engagement.• Assessment of aircraft position within the approved refueling envelope.• Analysis of closure rates, approach vectors, aircraft stability, and deviations from nominal procedures.• Ability to correlate video with other aircraft data if/as available (e.g. telemetry, fuel transfer rate, fuel state, and pilot inputs) to evaluate performance drivers.• Generation of objective performance scores and trend analysis across multiple training events.• Creation of visual performance assessment products for receiver pilot post-flight review of their performance during refueling, including graphical overlays, heat maps, event timelines, and immersive or interactive debrief environments.• Support for instructor review, adjudication, and refinement of automated assessments during initial deployment.The system should evaluate innovative approaches for integrating automated analytics with existing or future…

SBIR/STTR 은 미국 중소기업만 지원할 수 있습니다(Small Business Act 법정 요건). • 계열사를 포함해 상시 종업원 500명 이하 • 미국 시민 또는 영주권자 1인 이상이 50%를 초과해 직접 소유·지배 • 미국 내 사업장을 두고 주로 미국 내에서 사업을 영위할 것 • 수행책임자(PI)의 주된 근무처가 신청 기업일 것 출처: https://www.sbir.gov/faq/eligibility-requirements

Primary country

🇺🇸 United States

Also eligible

None

Foreign companies

No

Local entity

Required

Location condition

미국 내 사업장을 두고 미국 시민·영주권자가 50%를 초과해 소유한 중소기업만 신청할 수 있습니다(법정 요건).

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Official URL

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

Application URL

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

Last fetched

2026.10.07

Human review

Not reviewed — check the official announcement

First seen

2026.10.07

Data status

Auto-collected, not reviewed

AI enrichment

Needs verification