Adaptive AI-Driven Waveform Design

Name: Adaptive AI-Driven Waveform Design
Creator: Department of Defense
Published: 2026-07-01T12:02:18.642482+00:00
Keywords: SBIR

Department of DefenseOSD

AI Overview

Adaptive AI-driven waveform design for radar systems that autonomously optimize transmit parameters to counter electronic attack and interference in contested environments. The solution uses deep reinforcement learning to enable real-time waveform adaptation on edge-computing hardware while maintaining strict power and size constraints.

This summary is AI-generated from the official solicitation.

Key Details

Agency

Department of Defense

Funding Amount

—

Release Date

July 1, 2026

Due Date

August 19, 2026 (Closed)

Official Description

Modern radar operations face unprecedented challenges in increasingly congested and contested environments. Traditional radar systems rely on fixed or pre-programmed waveform libraries, making their transmissions highly predictable and susceptible to sophisticated electronic attack (EA). Near-peer adversaries now deploy advanced cognitive jammers and digital radio frequency memory (DRFM) systems that can rapidly analyze incoming radar pulses and generate deceptive or noise-based interference. Fu...

View on official source

Change History

Status ChangedAug 19, 2026 at 4:01 PM

Adaptive AI-Driven Waveform Design

Status changed from Open to Closed after topic disappearance

Q&A UpdatedAug 6, 2026 at 7:01 PM

Adaptive AI-Driven Waveform Design

# Summary for Prospective Applicants This Q&A clarifies that proposers must address whether solutions target jamming mitigation, clutter reduction, or both (requiring separate technical approaches), confirms the focus is ground-based conventional/Doppler radar rather than SAR or airborne systems, and asks whether Direct to Phase II proposals are eligible—critical distinctions that will shape technical approach and proposal strategy.

Status ChangedJul 22, 2026 at 1:03 PM