PROJECTED CMMC LEVEL REQUIREMENT
Level 2 (Self)
TECHNOLOGY AREAS
None
MODERNIZATION PRIORITIES
Integrated Network Systems-of-Systems
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Sustainment & Logistics
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Trusted AI and Autonomy
KEYWORDS
Optical Backscattering Reflectometer; OBR; Optical Time Domain Reflectometer; OTDR; Augmented Reality; AR; Low correlation OTDR; LC-OTDR; Pseudo Random Signal; PRS; Correlation Optical Time Domain Reflectometer; C-OTDR
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.
ITAR
The technology within this topic is restricted under the International Traffic in Arms Regulation (ITAR), 22 CFR Parts 120-130, which controls the export and import of defense-related material and services, including export of sensitive technical data, or the Export Administration Regulation (EAR), 15 CFR Parts 730-774, which controls dual use items. Offerors must disclose any proposed use of foreign nationals (FNs), their country(ies) of origin, the type of visa or work permit possessed, and the statement of work (SOW) tasks intended for accomplishment by the FN(s) in accordance with section 3.5 of the Announcement. Offerors are advised foreign nationals proposed to perform on this topic may be restricted due to the technical data under US Export Control Laws.
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
Real-time identification of defects (breaks, voids, misalignments, link degradation)
Pattern recognition and anomaly classification using historical signature databases
AI-Driven Virtual Assistants
On-device or network-connected chatbots providing guided maintenance workflows
Embedded AR interface for overlaying diagnostics on test hardware in real time
Advanced Troubleshooting Metrics
Spatial 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 m) and single mode (9/125 m) fiber types
GUI developed for intuitive field use across all operational conditions
Wavelength and Environmental Resilience
Operational 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)
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.
FEASIBILITY DOCUMENTATION: Offerors interested in participating in Direct to Phase II must include in their response to this topic Phase I feasibility documentation that substantiates the scientific and technical merit and Phase I feasibility described in Phase I above has been met (i.e., the small business must have performed Phase I-type research and development related to the topic, but from non-SBIR funding sources) and describe the potential commercialization applications. The documentation provided must validate that the proposer has completed development of technology as stated in Phase I above. Documentation should include all relevant information including, but not limited to technical reports, test data, prototype designs/models, and performance goals/results. Work submitted within the feasibility documentation must have been substantially performed by the offeror and/or the principal investigator (PI). Read and follow all of the DON SBIR FY26 Release 3 Direct to Phase II Broad Agency Announcement (BAA) Instructions. Phase I proposals will NOT be accepted for this topic.
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.
REFERENCES
"MIL-PRF-28800F; Test Equipment for use with Electrical and Electronic Equipment , General Specification for." http://everyspec.com/MIL-PRF/MIL-PRF-010000-29999/MIL-PRF-28800F_18207/
Villalba, Sergi; Casas, Joan R. "Application of optical fiber distributed sensing to health monitoring of concrete structures." Mechanical Systems and Signal Processing, Volume 39, Issues 1-2, August-September 2013, pp. 441-451. https://www.sciencedirect.com/science/article/abs/pii/S0888327012000283
Tosi, D.; Molardi, C.; Blanc, W.; Paix o, T.; Antunes, P. and Marques, C. "Performance Analysis of Scattering-Level Multiplexing (SLMux) in Distributed Fiber-Optic Backscatter Reflectometry Physical Sensors." Sensors, 20(9), 2595. https://doi.org/10.3390/s20092595
Liu, X.; Lun, H.; Fu, M.; Fan, Y.; Yi, L.; Hu, W. and Zhuge, Q. "AI-Based Modeling and Monitoring Techniques for Future Intelligent Elastic Optical Networks." Applied Sciences, 10(1), 363. https://doi.org/10.3390/app10010363
Cho, J. Y. et al. "DeepALM: Holistic Optical Network Monitoring based on Machine Learning," 2022 Optical Fiber Communications Conference and Exhibition (OFC), San Diego, CA, USA, 2022, pp. 1-3. https://ieeexplore.ieee.org/document/9748360
Chan, Eric Y.; Beranek, Mark W. and Harres, Daniel N. "A Novel Gb/s Transceiver with OTDR Built-in-test (BIT) for Health Monitoring of Local Area Networks." Optical Fiber Communication Conference and Exposition and The National Fiber Optic Engineers Conference, OSA Technical Digest Series (CD) (Optica Publishing Group, 2007), paper OWU2. https://ieeexplore.ieee.org/document/4348948
Straub, M. et al. "AI-based OTDR event detection, classification and assignment to ODN branches in passive optical networks." 49th European Conference on Optical Communications (ECOC 2023), Hybrid Conference, Glasgow, UK, 2023, pp. 1146-1149. doi: 10.1049/icp.2023.2469. https://ieeexplore.ieee.org/document/10484603
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