AI/ML Assisted Field Troubleshooting in Avionics Optical Network - SBIR Topic DON26BZ01-DV003
Disclaimer:
This topic was temporarily posted by the Department of War SBIR Program on March 2nd 2026 and removed the following day.
We believe this topic is planned to be released once the SBIR program is reauthorized; however, this topic may ultimately be modified or withdrawn.
Sign up below to be notified as soon as this topic is released again. In the meantime, we’d recommend you start planning to respond if within your capabilities.
Funding Amount:
Est. $2 Million.
Deadline to Apply:
Est. April 29th, 2026.
Objective:
Design, develop, and integrate a portable artificial intelligence/ machine learning (AI/ML)-enabled diagnostic module compatible with existing Optical Backscattering Reflectometer (OBR) and Optical Time Domain Reflectometer (OTDR) mainframes. The module will be engineered to support in-field optical network troubleshooting and management for high-speed communication systems.
Description:
Current airborne military (mil-aero) core avionics, electro-optical (EO), communications, and electronic warfare systems are experiencing continuous growth in bandwidth demand, coupled with stringent requirements to reduce Size, Weight, and Power (SWaP). Earlier-generation multimode optical fibers have replaced traditional shielded twisted-pair wire and coaxial cable, offering increased electromagnetic interference (EMI) immunity, higher bandwidth and throughput, and notable reductions in aircraft size and weight.
However, maintenance and troubleshooting of these advanced optical networks remain highly dependent on traditional telecommunication test equipment. Identifying and resolving faults—such as fiber breaks, fractures, and high-loss terminations—requires locating and distinguishing anomalies within meter-level precision, whereas modern avionic information-processing networks demand centimeter-level spatial resolution from source to detector.
Fault detection must extend beyond typical Weapons Replaceable Assembly (WRA) interfaces to identify:
Backplane/module degradation
Line replaceable module-to-optical transceiver faults
Polymer waveguide failures
Inline sensor (fiber grating) issues
Optical link loss across concatenated waveguide segments
Frequent airframe panel removal during fault isolation disrupts aircraft availability and mission readiness—especially for stealth platforms—highlighting the need for faster, more accurate, and less intrusive diagnostics.
To overcome these limitations, a portable AI/ML-enabled troubleshooting device is proposed to support field diagnostics across military airborne fiber-optic systems. The device will leverage next-generation reflectometry technologies and machine intelligence to enhance fault resolution precision and technician efficiency.
Key Capabilities:
AI-Augmented Fault DetectionReal-time identification of defects (breaks, voids, misalignments, link degradation)
Pattern recognition and anomaly classification using historical signature databases
AI-Driven Virtual AssistantsOn-device or network-connected chatbots providing guided maintenance workflows
Embedded AR interface for overlaying diagnostics on test hardware in real time
Advanced Troubleshooting MetricsSpatial resolution to centimeter scale across multiple fiber types
Predictive maintenance algorithms to reduce unplanned network downtime
Plug-and-Play Integration Fully compatible with existing portable OTDR/OBR mainframes
Support for both multimode (50/125, 62.5/125, 100/140 µm) and single mode (9/125 µm) fiber types
GUI developed for intuitive field use across all operational conditions
Wavelength and Environmental ResilienceOperational wavelength support: SWDM and CWDM
Designed for MIL-PRF-28800 Class 2 with select Class 1 enhancements
Operational temperature range: –40°C to +95°C
Resistant to mechanical shock, altitude variation, vibration, humidity, and thermal cycling
The device will build upon a fusion of legacy and emerging fiber-optic diagnostic technologies, including:
Optical Time Domain Reflectometry (OTDR)
Optical Backscatter Reflectometry (OBR)
Photon-Counting OTDR (PC-OTDR)
Low Correlation OTDR (LC-OTDR)
Pseudo Random Sequence (PRS) Correlation OTDR (C-OTDR)
Optical Frequency Domain Reflectometry (OFDR)
Who will win?
If you can achieve the objective above better than any other company on the market, you have a very high-likelihood of success and should apply.
Who is eligible to apply?
Any company that meets the following criteria:
For-profit company
U.S.-owned and controlled.
500 or fewer employees (including affiliates)
How Can BW&CO Help?
1) End-to-end support including, strategy, writing of the full proposal, and administrative & compliance support.
2) Proposal strategy and review.
3) Administrative & compliance support.
Request to talk with a member of our team by completing the form below: