DON26BZ01-DV042 — DIRECT TO PHASE II: AI/ML Assisted Field Troubleshooting in Avionics Optical Network

Award Maximum: $1,400,000 Period of Performance: 30 months (Base) + 12 months (Option) Phase Type: Direct to Phase II (DP2)

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 Detection o Real-time identification of defects (breaks, voids, misalignments, link degradation) o Pattern recognition and anomaly classification using historical signature databases

• AI-Driven Virtual Assistants o On-device or network-connected chatbots providing guided maintenance workflows o Embedded AR interface for overlaying diagnostics on test hardware in real time

• Advanced Troubleshooting Metrics o Spatial resolution to centimeter scale across multiple fiber types o Predictive maintenance algorithms to reduce unplanned network downtime

• Plug-and-Play Integration o Fully compatible with existing portable OTDR/OBR mainframes o Support for both multimode (50/125, 62.5/125, 100/140 µm) and single mode (9/125 µm) fiber types o GUI developed for intuitive field use across all operational conditions

• Wavelength and Environmental Resilience o Operational wavelength support: SWDM and CWDM o Designed for MIL-PRF-28800 Class 2 with select Class 1 enhancements o Operational temperature range: –40°C to +95°C o 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)

PHASE I: For a Direct to Phase II topic, the Government expects that the small business would have accomplished the following in a Phase I-type effort and developed a concept for a workable prototype or design to address, at a minimum, the basic requirements of the stated objective above. The below actions would be required to satisfy the requirements of Phase I:

Concept Development: Developed a concept for a viable prototype or design solution that addresses, at a minimum, the core technical and performance objectives outlined in the stated topic.

Feasibility Demonstration: Designed, developed, and demonstrated the technical feasibility of a low-cost, AI/ML-based plug-in module compatible with portable OBR and OTDR mainframes. The solution must meet applicable aviation support equipment requirements, including ruggedization, thermal compatibility, and interface standards.

Performance Modeling and Simulation: Modeled and simulated the plug-in module's performance under high-speed application conditions, validating its functionality across relevant operational scenarios and wavelengths.

Design Packaging: Delivered a conceptual packaged design of the plug-in module, incorporating mechanical footprint, connector interface, and Graphical User Interface (GUI) considerations to support seamless integration into current field-deployable test equipment.

PHASE II: Design, construct, and validate a functional AI/ML-enabled plug-in module prototype. Focus on transitioning the concept design into an operational system capable of meeting the rigorous demands of military optical diagnostics.

Include in the Prototype Design and Fabrication the following:

• Engineering of a robust plug-in module design based on Phase I feasibility studies and modeling outcomes.

• Integrating AI/ML processing hardware, signal acquisition architecture, and interfaces into a fully packaged prototype.

• Ensuring form-factor compliance with portable OTDR and OBR mainframes, including connector integrity, mechanical footprint, and GUI usability.

• Compiling system-level test data and validating against entry criteria for Technology Readiness Level (TRL) 6.

PHASE III DUAL USE APPLICATIONS: Collaborate with defense avionics industries as well as support equipment companies to accelerate transition to production.

Commercial telecommunication systems, fiber-optic networks, and data centers will benefit from the development of the AI/MIL based OBR and OTDR. These applications will be able to easily test/diagnose optical networks.