Twinleaf LLC — Department of Defense SBIR Phase II: AF20A-T002
Twinleaf LLC — SBIR Phase II award from Department of Defense.
Phase II SBIR prototype / development signal
- Phase II is where Department of Defense funds deeper R&D after feasibility. Incumbents with Phase II history are serious competitors on adjacent topics.
- Use this award as past-performance context and to map customer organizations for STRATFI/TACFI-style transition planning.
- At $1,798,808, this is a large obligation for typical SBIR Phase sizing — worth reviewing for scope breadth and teaming opportunity.
- Topic code AF20A-T002 links this award to a solicitation family — search the same topic stem for incumbents and recompete timing.
- Amount
- $1,798,808
- Agency
- Department of Defense · Defense Advanced Research Projects Agency
- Program / Phase
- SBIR · Phase II
- Topic
- AF20A-T002
- Solicitation
- 20.A
- NAICS
- —
- Place of performance
- NJ
- Period
- 2023-05-18 → 2025-05-21
Description
Navigation of aircraft using the crustal magnetic field variation of the earth is a novel and developing technique for use in GPS-denied environments. Location estimation is accomplished by matching the magnetic field measurements in flight to a specific track on a magnetic map of the globe. Atomic scalar magnetometers are ideally suited for use on aircraft because they are not sensitive to aircraft motion; they measure the total field instead of the vector projections. Quantum magnetometers employing alkali metals are also far more accurate than solid state devices such as fluxgates, nitrogen vacancy diamond, and magnetoresistive sensors. That accuracy can be used to improve the time to acquire a unique location and reduce the location uncertainty. This project develops the ideal sensor for magnetic navigation by combining a novel physical operating technique with rugged wafer-scale packaging. Crucially, the new sensor design operates well at all flight headings whereas previous sensors do not work when pointing in certain directions. The magnetometer will also target a small 1 cc size, making it easy to implement on platforms of all sizes.