Real Time Enhanced Fine Tracking in Directed Energy Applications

STTR · Phase: BOTH · Topic DAF26TZ05-NV005 · Solicitation 26.TZ

Current tracking capabilities in DE utilize 2D imagery. Low flying targets against cluttered backgrounds (e.g., drones) present a challenging tracking environment for track algorithms that leverage 2D information alone. A current tracking algorithm might use something like a Fitts correlation tracker [2], which correlates features in the scene with a known template of the target. This requires target identification followed by reference to a look-up table to determine the proper template to use with the correlation tracker, which can be difficult with 2D imagery, as a 2D image of the target will only provide a projection of the target image along the optical axis. 3D coherent imaging with digital holography [3,4] provides a solution for the problems associated with 2D imaging that are described here. Emerging coherent 3D imaging modalities provide complex-valued images (referred to as 2.5D images) with amplitude corresponding to a conventional 2D image and phase corresponding to the range to the target. The range images themselves (which describe the range to the target for each transverse pixel) are highly robust to scintillation and speckle [5,6]. Going further, novel methods in image restoration that include a combination of physics-based [7-11] and machine-learning [10,11] models can provide effective and computationally efficient ways to remove the anisoplanatic distortions in the image. Note that alternative 3D imaging methods do exist (e.g., Geiger mode 3D imaging with avalanche photodiodes [5]). The Phase I effort should include an analysis of existing methods before selecting one to explore for the given application. The topic proposed here is nominally focused on the fine track portion of the DE kill chain, though the technology could be used for acquisition/coarse tracking as well. We briefly summarize the key features of fine tracking in DE, which performers should keep in mind when designing systems: For fine tracking, the atmosphere and aero-optic disturbances impose phase aberrations that can severely degrade imagery. Importantly, tracking at this stage influences aimpoint maintenance, which requires fine track loops to run at much higher framerates (> 1 kHz) to keep up with the changing atmosphere while employing narrower fields of view (fractions of a degree). 3D imaging provides a path forward for enhanced pose estimation and aimpoint maintenance in the context of fine tracking. With regards to illumination for fine tracking, active coherent illumination can result in non-uniform illumination patterns on target, due to scintillation, and in speckle noise in received target imagery. Partially coherent (or multiple coherent) illuminators can reduce the effects of these two noise terms, but at the cost of the ability to perform coherent imaging and/or additional illuminators. On a similar note, coherent imaging techniques (such as digital holography and phase retrieval) can allow for digital image correction of anisoplanatic phase errors using physics-based [7-11] and machine-learning-based [10,11] image reconstruction algorithms. Note that active illumination, in general, enables tracking technology that can perform in day or night. In general, performers should be aware of the general requirements for fine tracking and should tailor designs to the technology best suited for the application. This topic seeks the development and testing of a computationally efficient processing pipeline that meets the requirements for real-time integration into a directed energy system. The goals are to design (Phase I) and demonstrate (Phase II) the processing pipeline for a 3D imaging system that can operate effectively over long standoff ranges through aerooptics/turbulence with extended, non-cooperative targets against cluttered backgrounds. The Phase I effort will design the 3D measurement technique, corresponding algorithms, and a concept for the integrated hardware. This should include analysis of the latency and through…

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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Generated by local:rules-v1 · 4h ago

The announcement does not say what has to be submitted, so the disclosure exposure cannot be judged. the scope of the material requested is not stated. The awarding body is U.S. Department of War — USAF. 8 fields could not be read and must be checked in the announcement and the grant agreement.

This assessment is derived from the stored announcement, document and contract fields. Anything the source does not state is marked "needs verification" — it never asserts that your idea will be taken. Generated by local:rules-v1 · 4h ago

Official URL

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

Application URL

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

Last fetched

2026.08.20

Human review

Not reviewed — check the official announcement

First seen

2026.08.20

Data status

Auto-collected, not reviewed

AI enrichment

local:rules-v1 · 4h ago