This post is also available in:
עברית (Hebrew)
Modern military operations depend heavily on the electromagnetic spectrum. Radar systems, communications networks, GPS signals and electronic warfare equipment all compete for access to this invisible environment. As battlefields become more electronically contested, forces must identify hostile emissions, understand what they are, and react within seconds, often faster than a human operator can process the information.
A recent flight test demonstrated a new approach to that challenge. L3Harris Technologies successfully tested its Distributed Spectrum Collaboration and Operations (DiSCO) ecosystem together with Shield AI’s Hivemind autonomy software, enabling unmanned aircraft to detect electromagnetic threats, analyze them and respond autonomously during flight.
Rather than acting as a single electronic warfare system, the technology serves as a battle management architecture that links multiple electronic warfare assets into a shared network. Information collected by one platform is immediately distributed across the system, creating a common picture of the electromagnetic environment. This allows multiple unmanned aircraft to coordinate their actions instead of operating independently.
According to Interesting Engineering, the live demonstration was conducted using the company’s Green Wolf launched-effects platform equipped with the company’s software-defined Deceptor electronic warfare payload. During the mission, the payload detected and characterized previously unknown electromagnetic threats, then shared the information through the tech’s network. The software used that data to make real-time decisions, autonomously directing follow-on unmanned aircraft around hazardous areas without requiring operator intervention.
One of the system’s key advantages is the combination of sensing and decision-making. Detecting a radar or electronic attack is only part of the challenge; aircraft must also determine how to respond before entering the threat zone. By continuously processing electronic intelligence from multiple platforms, the autonomy software can rapidly identify safer flight paths and redirect other drones while the mission is still underway.
The architecture is also designed to be vendor-agnostic, allowing electronic warfare systems from different manufacturers to exchange information through the same network. This open approach makes it easier to integrate new sensors, payloads and autonomous platforms without redesigning the entire system.
Electronic warfare has become one of the most important elements of modern defense operations. Rather than relying solely on kinetic weapons, militaries increasingly seek to detect, jam, deceive or avoid hostile electronic systems before they can engage friendly forces. AI-enabled battle management platforms such as this aim to accelerate this process by reducing the time between sensing a threat and responding to it.
Following the successful flight test, the companies plan to expand the system’s autonomous capabilities and support additional electronic warfare missions. As unmanned aircraft take on more complex battlefield roles, distributed electronic warfare networks that allow platforms to sense, share information and coordinate their actions in real time are expected to become an increasingly important part of future military operations.
