Sensor Technology

The Fiddler program is training an artificial intelligence (AI) algorithm to synthesize artificial Synthetic Aperture Radar (SAR) images at any arbitrary look angle, frequency, and polarization based on a few examples of real images. These artificial images are used to train and improve the performance of Automatic Target Recognition (ATR) algorithms. This capability allows the government to collect a small amount of SAR imagery on a desired target and then rapidly develop new SAR-based ATR algorithms which are effective at detecting that target. Technology developed under this program will transition to the Naval Research Laboratory and a U.S. Navy program office.

The goal of the Ouija program is to quantify the High Frequency (HF) noise environment in space and improve the characterization of the ionosphere in support of warfighter capabilities. Ouija intends to make ionospheric measurements of unprecedented granularity using ground equipment and satellites in very low earth orbit (VLEO) to improve ionospheric models and better predict long-range HF propagation. Ouija technology will result in improved performance and characterization of radars and communication systems that operate in the HF band. Technology developed under this program will transition to the Services.

The Dynamic Optimization for Defense of Ground bases with Electromagnetic warfare (DODGEball) program will develop algorithms for optimization of non-kinetic countermeasures for efficient and effective resource management in extended campaign warfare. DODGEball will optimize heterogeneous applications of electromagnetic warfare for the defense of surface forces and infrastructure for long duration campaigns. Technology developed under this program will transition to the Services. Beginning in FY 2026, this program will be funded in PE 0603467E, Project DAT-02.

The Cancun program will create distributable nodes to measure the radio high frequency (HF) environment for improved war fighter situational awareness. Cancun will enable cost-effective wide-area deployment of low size, weight, power, and cost (SWaP-C) nodes. Cancun will also develop the command and control (C2) network and planning tools required to address the challenge of coordinating large numbers of Cancun nodes deployed over distances of well over 1000 kilometers. The Cancun nodes will measure the state of the ionosphere using a sounding function, as well as record and relay portions of the HF radio band for analysis. The mission planning tool will be developed with war fighter input to optimize functionality. Technologies developed under the Cancun program will transition to the Services. Beginning in FY 2026, this program will be funded in PE 0603467E, Project DAT-02.

The Thermal Imaging Technology Experiment-Recon (TITE-R) program developed and demonstrated complementary sensing modalities, advanced processing, and low size, weight, and power which more closely represents an objective capability. TITE-R developed sensors and software automation capable of supporting future operations implemented on small (< 250 kg) satellites. TITE-R also developed mission software to support automated on-board processing and simplified operator tasking. TITE-R rapidly developed and tested early-to-space prototype system payloads made available to transition partners to integrate with space vehicles and conduct experimentation. Technology developed by this program transitioned to the Services and other government agencies.

The Painter program seeks to create revolutionary advancements in laser technologies for future active optical systems. Painter will translate efficiency benefits from critical laser components into compact optical sources. The objective of Painter is to simultaneously increase the power and decrease the size of laser sources compared to state of the art. Aggressive packaging objectives will be met by overcoming the thermal management challenges of state-of-the-art lasers. Painter development is guided and constrained by spectral properties required to support multiple mission applications. Technologies from Painter will transition to the Services.

Based on recent developments in small synthetic aperture radar (SAR) satellites in commercial industry, there are new opportunities to experiment with novel SAR-related concepts. The goal of the Distributed Radar Image Formation Technology (DRIFT) program is to demonstrate advanced capabilities enabled by a cluster of SAR satellites flown in formation. DRIFT seeks to acquire data from SAR satellites flown in formation and to demonstrate novel processing algorithms on this data. This will expand the utility of small SAR satellites, including commercial satellites, for military applications. Technology developed under this program will transition to the Services.

Photocathodes can be found in devices such as photomultiplier tubes, image intensifiers, high-power electronics, and even free electron lasers. Photocathodes typically use low-work function metals or semiconductors and are applied in sub-micron thicknesses on planar surfaces with millimeter to centimeter-scale areas. In addition to size and geometry limitations, current materials are fragile and require special handling in ultra-high vacuum conditions. The Large Area Photocathode (LAP) program seeks to overcome these limitations by developing manufacturable photocathode material systems with high quantum efficiency that can be produced in large areas and curved geometries with substantial lifetimes. New materials and assembly methods, leveraged from the Ultra-Wide BandGap Semiconductors (UWBGS) program (budgeted in PE 0602716E, Project ELT-01) will be refined and tested through the application of large area photocathodes to a high current, fast electron device prototype. The prototype will demonstrate material feasibility and enable new classes of fast electron devices with relevant applications. Technology developed under this program will transition to the Services. Beginning in FY 2026, this program will be funded in PE 0603467E, Project DAT-02.

The X-ray Extreme-range Non-imaging Analysis (XENA) Program intends to discover new methods for long-standoff X-ray characterization through the development of data processing algorithms. Based on methods explored in the Advanced Tools for Modeling and Simulation program (budgeted in PE 0601101E, Project CCS-02), XENA will enable the processing of imperfect radiography datasets to gain useful insights. Algorithm enhanced radiography datasets could be valuable in numerous fields ranging from regulatory industries to quality control. The specific enhancements XENA intends to focus on include improvements to overcome low contrast and motion blur to mimic data collected in real-world environments. Technology developed under this program will transition to the Services, other U.S. Government organizations, and commercial industry. Beginning in FY 2026, this program will be funded in PE 0603467E, Project DAT-02.