Objective

Demonstrate the utility of using artificial intelligence/machine learning (AI/ML)-driven spatial and spectral techniques to improve the resilience of fire control and tactical squad communication systems in contested electromagnetic environments.

Description

Future conflicts are anticipated to involve significant use of autonomous unmanned aircraft system (UAS) weapons combined with aggressive electromagnetic interference and adversary geolocation of radio frequency (RF) emissions. Spatial and spectral management overlaid on fielded tactical waveforms and navigation signals will improve soldier lethality and survivability by providing awareness of enemy electromagnetic spectrum operations and enabling communications with reduced risk of detection.

Phase I

During Phase I, successful proposers shall conduct a proof-of-concept study to show feasibility of their technical approach to improve the resilience of RF subsystems throughout the kill chain to adverse electromagnetic environments. Validation of the proposed approach can be implemented through simulation or prototype measurements.

Metrics to be considered should include communication and radar performance metrics when AI/ML techniques are implemented in the antenna (e.g., improved dynamic range, signal to interference & noise ratio (SINR), range or detection/observability, or data rates). Phase I performers will deliver a proposed system approach for detailed design and demonstration during Phase II, including plans for how autonomous behaviors using AI/ML will be trained and evaluated for safety and effectivity.

Phase II

Develop a prototype digital antenna system that can demonstrate the advantages of the offeror’s digital antenna technology in a laboratory environment. Test conditions for showing the effectiveness of any AI/ML techniques should be designed to be representative of tactical operations to the extent practical in a controlled environment using inputs from Army concepts of employment.

The Phase II performer will demonstrate an AI/ML-driven antenna system in a laboratory environment to show spatial and/or spectral interference mitigation in response to the electromagnetic environment. The Phase II deliverables will include a comprehensive technical report of the demonstration design, and commercialization/transition plan for department of defense (DoD) use

Phase III

Phase III will consist of completing the maturation of the technology developed in Phase II for transition into a fieldable Army mission capability. This shall be accomplished through production of prototype systems to support further development and commercialization. Phase III selections shall have adequate support from an Army prime or industry transition partner identified during earlier phases of the program.

The proposer shall work with this partner to fully develop, integrate, and test the performance and characteristics of the design for integration onto the target transition system. Adaptive/intelligent interference mitigation techniques may also have commercial application in congested wireless spectrum environments to increase throughput of commercial communications systems and reduce RF interference impacts for sensors such as automotive radars.

Submission Information

For more information, and to submit your full proposal package, visit the DSIP Portal.

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