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DoW/DTRA · DoW SBIR 2027 BAA

DTR27BZ02-NV002 — Remote UAS-based X-Ray for Device Assessment in CBRNE Environments

Pre-Release | released 2026-11-04 | opens 2026-12-02 | closes 2027-01-06 | CMMC Level 1, SBIR

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TPOC: Steve Waugh <[email protected]>

Keywords: Unmanned Aerial System (UAS): Explosive Ordnance Disposal (EOD): Remote Render Safe: Precision Aiming: Operational Standoff: Disruptor Payload: CBRN Environments: Remote Command and Control: Trusted Autonomy: Small-Unit UAS

Technology areas: Chem Bio Defense, Sensors

Objective

Develop a novel stand-off X-ray capability by integrating appropriate x-ray transmitter and x-ray receiver capabilities into multiple cooperating UAS systems to enable remote threat device imaging capabilities from a safe distance away from potential Chemical, Biological, Radiological, or Nuclear (CBRN) environments.

Description

DTRA is in need of technical innovations associated with Warfighters performing long range WMD device assessment and characterization from a safe distance outside of potentially CBRN contaminated environments. Explosive Ordinance Disposal (EOD) definitions and terms are commonly used by many nations and exist on the public internet including steps involving EOD detection, assessment, identification, field evaluation, render safe, recovery and disposal. Current device assessment is manual, requiring personnel to approach closely and manually move x-ray transmitters and x-ray receivers around an unknown device to perform the required assessment mission. Current stand-off capabilities are typically ground robots manually driven a short distance which may be safe for some unexploded ordinance (UXO), but are not safe for suspected WMD warheads. Recent UAS innovations associated with coaxial form factor systems that can perch or land as part of their mission flight profile appear to offer a novel approach to conducting bi-static x-ray image collection. STATE OF TECHNOLOGY. Current Portable digital radiography systems that depend on hand- or robot-emplacement of a source and flat-panel detector near the device are limited in a CBRN environment. There is no current technology solution that can generate diagnostically useful transmission images (sufficient penetration of ordnance casings plus resolution of fine fuse features such as wires, switches, or delay elements) without any ground contact or personnel entry into the contaminated zone. Mobile x-ray transmitters and various options for exposing images, and stitching multiple images together to create a 3-D assessment of an unknown device exist, but they are generally hand-carried and emplaced. Complex mathematics and algorithms for capturing and rendering X-ray results from multiple simultaneously moving transmitters and receivers each with potential uncertainties in position and angle are limited. Tactical UAS systems are generally small, carry lighter payloads, do not have open architectures for payloads, and payload options are generally difficult and limited to the bottom side to integrate without adversely affecting flight profiles. Robotic x-rays exist but are typically fixed, large and devices are brought to them and put on a turntable. This topic is for x-rays done in the field, at 5km distances, without moving the threat device. No UAS-based x-ray capability currently exists.

Phase I

Design a novel stand-off X-ray capability concept that would integrate portable x-ray transmitter and receiver capabilities into multiple cooperating UAS systems. Create an in silico model of system performance with mathematical assessment of anticipated image quality as a function of time, motion, and navigation uncertainties. A functional transmission X-ray source (high-voltage generation, cooling, radiation shielding) plus a suitable detector must be integrated while preserving flight stability for sharp imaging, supporting open real-time data architectures.

Phase II

Build one working prototype of proposed system to demonstrate capability to collect data for post-processing at a later date. Prototype design should look to fill persistent and newly heightened technical gaps to include: lightweight, high-flux (preferably pulsed) X-ray sources and detectors suitable for prolonged airborne carriage; robust real-time algorithms for motion-compensated multi-view reconstruction from independently flying platforms; methods to extract fuse-function information from low-signal, limited-angle, or single-pass data; sealed or disposable system architectures that eliminate the need for recovery of contaminated hardware; and practical techniques that achieve usable diagnostic quality at greater effective standoffs while still resolving internal mechanisms without any ground presence.

Phase III / dual use

Extend Phase 2 capabilities to scale performance of missions at multiple sites, allowing for multiple swarming transmitters and/or receivers spread over time and space. Demonstrate ability to generate integrated X-Ray image results rapidly, on location in near-real-time during or soon after completion of swarming activities.

References

  1. Naval Surface Warfare Center (NSWC) / Indian Head Division. https://www.navsea.navy.mil/Home/Warfare-Centers/NSWC-Indian-Head/
  2. Naval Sea Systems Command (NAVSEA) / Indian Head Division. https://www.navsea.navy.mil/Home/Warfare-Centers/NSWC-Indian-Head/What-We-Do/
  3. RAND study “Army Explosive Ordnance Disposal in Large Scale Combat Operations”, Jennifer Lamping Lewis, et. al. 2024. Download at ttp://www.rand.org/t/RRA2078-2
  4. Chandra, R., Kaczmarek, J., & Neumann, M. (2025). X-ray image generation for robotic radiography: A case study on motion blur in drone-based wind turbine inspections. Journal of Nondestructive Evaluation, 44(1), Article 12. researchgate.net
  5. University of California - Santa Barbara. "X-ray eyes in the sky: Drones and WiFi for 3-D through-wall imaging." ScienceDaily. ScienceDaily, 19 June 2017. <www.sciencedaily.com/releases/2017/06/170619144830.htm>.
  6. Example UAS with modular architecture - Coaxial Spartan NX-30 Ascent UAS, https://www.robinsonheli.com/unmanned/uas/spartan
  7. Lee, H., et al. (2024). “A Drone-Driven X-Ray Image-Based Diagnosis of Wind Turbine Blades for Reliable Operation of Wind Turbine.” IEEE Access, 12, 56141–56158. DOI: 10.1109/ACCESS.2024.3388494.
  8. Lee, J., et al. (2023). “X-ray image-based flight path planning model of UAVs for non-destructive inspection of wind blades.” ITC-CSCC 2023. DOI: 10.1109/ITC-CSCC58803.2023.10212472.
  9. Lee, H., et al. (2025). “Autonomous Drone Flight Using Object Detection in X-Ray Images for Wind Turbine Blade Internal Inspection.” ECAI 2025, pp. 5319–5326. DOI: 10.3233/FAIA251469
  10. Meere, B., et al. (2025). “X-ray Image Generation for Robotic Radiography: A Case Study on Motion Blur in Drone-Based Wind Turbine Inspections.” Journal of Nondestructive Evaluation, 44, 139. DOI: 10.1007/s10921-025-01279-6
  11. University of North Carolina at Chapel Hill (2020). Mobile and Free-Form X-Ray Imaging Systems and Methods, U.S. Patent 10,539,708.
  12. Novel Coaxial UAS, Ascent AeroSystems. Spartan Unmanned Aircraft System (UAS) – System Description and Specifications. Website: https://ascentaerosystems.com/ (product/system pages for the Spartan UAS)

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