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Modern military operations rely heavily on understanding and shaping the electromagnetic environment. Radar emissions, jamming signals, and electronic intelligence streams can shift rapidly, leaving commanders with limited time to detect, classify, and respond. Two new systems introduced by Thales target this challenge directly, offering faster sensing and automated signal analysis to support air, land, and maritime missions.
A core problem for today’s electronic warfare (EW) units is the volume and complexity of data they must interpret. Radar signals vary widely in frequency, pulse structure, and behavior. Mapping this environment used to require large platforms and long processing times. CURCO, a compact EW payload, is designed to solve this by giving multiple platforms—drones, aircraft, naval vessels, and ground vehicles—a plug-and-play sensor for rapidly scanning radar emissions. The payload detects and geolocates signals across a broad spectrum, producing real-time maps of potential threats. During French Navy exercises, the system demonstrated seamless integration with various mission systems and showed that small platforms can now take on roles traditionally reserved for larger, dedicated aircraft. An optional jammer function extends its utility by allowing operators not only to detect hostile radars but also to disrupt them if needed.
According to NextGenDefense, the second system, Golden AI, addresses the bottleneck that occurs after signal collection: the analysis phase. EW analysts often face hours of radar recordings that must be manually sorted, compared to historical libraries, and validated before threat assessments can be updated. Golden AI automates much of this workflow. By training machine-learning models on historical radar patterns and applying them to new mission data, it can accelerate radar identification tasks by up to four times while standardizing results.
The combination of automated analysis and rapid sensor deployment strengthens situational awareness in contested electromagnetic environments. Faster identification of hostile radars supports improved air-defense readiness, while automated cataloging of signals helps maintain national EW databases—critical for countering evolving threats.
Tested during operational exercises, both tools aim to reduce operator burden and shorten reaction times. As electronic warfare becomes increasingly central to multi-domain operations, systems like CURCO and Golden AI demonstrate how sensing and AI-driven analysis can work together to deliver a more agile and resilient electromagnetic posture.
