ARETE ASSOCIATES — Department of Defense SBIR Phase I: AF222-0010
ARETE ASSOCIATES — SBIR Phase I award from Department of Defense.
- Amount
- $149,992
- Agency
- Department of Defense · Air Force
- Program / Phase
- SBIR · Phase I
- Topic
- AF222-0010
- Solicitation
- 22.2
- NAICS
- —
- Place of performance
- CA
- Period
- 2023-01-12 → 2023-10-12
Description
Star trackers are ubiquitous in space applications, providing accurate absolute pointing calibration to satellites and other space based systems. However, most celestial scenes are extremely sparse, featuring relatively few stars on a fixed black background, wasting power and data processing on nearly featureless images. The inefficient data usage combined with motion blur associated with platform motion limits typical star trackers to operation below 5 degrees per second. This low operational speed: can lead to lost in space failure modes; limits application to highly dynamic platforms; and requires intermittent recalibration for some platforms, which reduces up time. Event cameras excel at imaging highly dynamic sparse scenes with no motion blur, and are an emerging technology that Areté believes will be an enabling technology for next generation star trackers. Areté will establish the viability of event cameras for star tracking applications through a series of laboratory based calibrations with current generation state-of-the-art event cameras and will design a brass-board system known as the Areté Neuromorphic Star Tracker (AN-ST). The AN-ST will be based on existing Areté algorithms for event camera processing and star catalog mapping algorithms developed for previous programs. If the current generation technology is viable, the AN-ST will enable a new generation of extremely fast attitude determination systems. If current technology is insufficient to meet the requirements for this application, Areté will provide a roadmap for further development, and partner with event camera manufacturers to encourage sensor development. The AN-ST will build on Areté’s experience in accurate object tracking with event camera data, and existing codebases for stellar navigation, allowing an efficient trade study focused on investigating novel components and not recreating existing algorithms/techniques