Embedding Physical AI at the RF Edge for Defense Systems

Defense RF platforms are evolving from “sense-and-stream” architectures to “sense-think-act-communicate” Physical artificial intelligence (AI) architectures where inference and control occur as close to the antenna as possible to shorten decision loops and improve performance in contested environments. This shift is driven by rapidly increasing spectrum and waveform complexity, paired with strict size, weight, power and cost (SWaP-C) constraints, and the growing need for trusted microelectronics in sensitive defense applications.

In practical terms, operators need RF systems that can adapt to dense spectral occupancy, interference, jamming/spoofing, multipath and complex multi-function sensor operations without relying on high latency backhaul to centralized compute. As spectrum becomes more crowded, and decisions more real time, defense systems must redesign RF architectures to achieve in-theatre electromagnetic advantage with closed-loop, edge-resident intelligence.