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Find similar grantsAdaptive AI-Driven Waveform Design is sponsored by U.S. Department of the Army. This opportunity supports mission-aligned projects and measurable outcomes.
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Adaptive AI-Driven Waveform Design Adaptive AI-Driven Waveform Design AI Analysis Solicitation Details Details SBIR Documents ( 1 ) Documents ( 1 ) SBIR Opportunity Analysis The Department of Defense, through the Office of the Secretary of Defense SBIR program, is seeking proposals to develop an AI/ML-controlled radar waveform generator that dynamically designs and optimizes waveforms in real time.
Performers will utilize deep reinforcement learning to adjust key waveform parameters such as frequency, modulation, pulse repetition frequency, and bandwidth to evade jamming and mitigate interference.
Phase I focuses on a feasibility study and software prototype in a simulated radio frequency environment, while Phase II requires implementing the controller onto edge-computing hardware with software-defined radios for real-time testing. Ultimately, Phase III aims to transition the technology into operational Army radars and commercial systems, such as autonomous vehicles.
Proposals must be submitted by the application deadline of August 19, 2026, at 4:00 PM Eastern Time. This Army SBIR solicitation (OSW26BZ04-DV009) seeks to develop an AI/ML-controlled radar waveform generator that dynamically adjusts frequency, modulation, and coding in real time.
The goal is to optimize radar performance and evade advanced jamming, digital radio frequency memory (DRFM) systems, and radio frequency interference (RFI) in contested environments. The project leverages deep reinforcement learning (DRL) to enable a neural agent to autonomously synthesize and optimize transmit waveforms based on real-time spectral observations.
Because this capability requires micro-second execution, the models must be optimized for edge-computing architectures, such as software-defined radios (SDRs) and field-programmable gate arrays (FPGAs), while adhering to strict size, weight, and power (SWaP) constraints.
The project is structured into three phases: - **Phase I:** Conduct a feasibility study and develop a simulated software proof-of-concept demonstrating improved target detection over traditional fixed-waveform baselines. - **Phase II:** Implement and optimize the AI/ML controller onto physical, edge-computing hardware (SDR/FPGA) and deliver a fully integrated prototype for laboratory or field testing.
- **Phase III:** Transition the technology into military platforms, such as UAS sensors, ground surveillance, and AESA radars. This technology has dual-use potential for commercial automotive radar, air-traffic control, and dynamic spectrum sharing.
The topic is restricted under ITAR/EAR regulations, requires a CMMC Level 2 (Self) certification, and falls under the "Trusted AI and Autonomy" and "Integrated Sensing and Cyber" modernization priorities. Related SBIR/STTR Opportunities View Documents Access 1 attachments Source System Official Link Application Due Aug 19, 2026
According to the current listing, eligibility includes: Small businesses. Restricted under ITAR/EAR regulations and requires CMMC Level 2 certification. Confirm the full requirements in the official notice before applying.
The published deadline was August 19, 2026, which has passed. Check the official notice for any future application windows before investing time in a proposal.
Adaptive AI-Driven Waveform Design is funded by U.S. Department of the Army. Verify program details on the funder's official page before applying.
Start from the official opportunity page linked in this listing — it carries the sponsor's submission instructions.
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