DIRECT TO PHASE II: Advanced Multi-User Signal Separation for Tactical Waveforms

SBIR topic DON27BZ02-DV028 (U.S. Department of Defense – Navy), Phase I and II. Open to U.S. small businesses. Opens: December 2, 2026. Closes: January 6, 2027. The Program Office championing this effort is PMW/A 101 that manages and delivers advanced, secure tactical communication systems for naval platforms. A core mandate of this office is to continuously integrate next-generation capabilities that enhance waveform resilience, increase spectral efficiency, and ensure robust connectivity for warfighters operating in highly congested and contested electromagnetic environments. The technology developed under this SBIR Direct to Phase II topic is intended to transition directly into the PMW 101 portfolio of tactical radio systems. In modern tactical networks, the proliferation of friendly assets creates a dense signal environment where simultaneous transmissions on the same frequency cause multi-user collisions and limit operational effectiveness. This problem is exacerbated in contested domains where very low Signal-to-Noise Ratios (SNRs) are common. Current baseline receiver systems typically treat these overlapping friendly signals as insurmountable noise. Because legacy systems lack the ability to untangle these collisions, they simply drop the packets or fail to decode them entirely, which severely limits network throughput and the real-time data exchange required for mission-critical operations. To overcome these limitations and maintain a critical operational advantage, this SBIR Direct to Phase II topic seeks the development of an advanced signal processing core capable of robust multi-user signal separation for tactical waveforms. By enabling non-orthogonal multiple access-like schemes, this capability will significantly increase network capacity and user count without requiring additional spectrum. The goal is to deliver high-quality soft signal likelihoods recovered from simultaneous-user collisions to downstream soft-decision decoding algorithms. To…