Artificial intelligence (AI) is one of the world’s most advanced technologies and in recent years it has been rapidly developed, with applications across many subjects achieving fruitful results. With the development of technologies such as the Internet of Things, autonomous driving, and smart industries, the perception and cognition of the external environment has become increasingly important. However, the use of a large number of communications and sensor equipment has led to a shortage of spectrum resources and serious mutual interference. It is very difficult to carry out effective electromagnetic signal perception and cognition in a complex electromagnetic environment because the signals are diverse and dynamic, and the parameters often change. Artificial intelligence technology, in particular deep learning (DL), has been proven to solve electromagnetic signal perception and cognition problems, including high model robustness, and to deliver excellent performance.

Dealing with increasingly scarce spectrum resources and increasingly complex electromagnetic environments has become a significant challenge. Various concepts, such as intelligent spectrum sensing, communication radar integration, and intelligent cognition of electromagnetic signals have all emerged as potential solutions to the problems of tight spectrum resources. The transformation of these concepts and methods into practical applications is inseparable from the development of AI technology. The continuous development of various technologies combined with artificial intelligence provides powerful means of machine and environment interaction. This combination represents not only a breakthrough in traditional technology, but also the expansion and improvement of artificial intelligence technology.

The goal of this Special Issue is to help us to understand the industry trends of development in electromagnetic signal sensing and cognition, master the latest technology, broaden research horizons and promote academic progress, and to develop efficient applications of technological achievements. We welcome experts and scholars engaged in related technical research and professional technical personnel to contribute. We welcome both original research and review articles.

Potential topics include but are not limited to the following:

• DL/AI-based spectrum sensing and spectrum management
• DL/AI-based electromagnetic signal/target intelligent cognition
• Intelligent sensing of communication/radar waveforms
• Intelligent cognition of communication/radar interference
• Intelligent cognition of radio frequency fingerprints
• Adversarial attacks and defenses in intelligent sensing and cognition
• Spectrum efficient intelligent cognition for green communications
• Intelligent sensing and cognition for unmanned aerial vehicle (UAV) networks