The Development From Adaptive to Cognitive Radar Resource Management

Cognitive radar can be defined as [1]: A radar system that acquires information, knowledge, and understanding about its operating environment through online estimation, reasoning and learning, or from datasets comprising context. A cognitive radar then exploits the acquired information, knowledge, and understanding to enhance information extraction, data processing, and radar management. Implicit in this definition is the implementation of perception-action cycles that are predominantly recognized as a defining feature of cognitive radar. As is evident from the variety of living species, the extent to which information, knowledge, and understanding is acquired and exploited can vary greatly. Consequently, a single feature qualifying a radar as cognitive does not exist. Instead cognition can be visualized as a continuous spectrum with varying degrees of cognitive capability [2]. A cognitive radar ultimately finds that the information present in a single radar dwell is insufficient to effectively control the available degrees of freedom. Therefore, a cognitive radar attempts to preserve information, knowledge, and understanding exploited from any available source, be it processed radar data acquired over extended time periods, context, or learning. Multifunction radar (MFR) is a particularly attractive recipient for cognitive radar techniques. An MFR, ideally enabled by arbitrary waveform generation and electronic beam steering, is capable of executing many tasks that support differing radar functions. Radar resource management is a vital enabling technology for an MFR, as it enables an effective control of the transmitter degrees of freedom, thus unlocking the full potential of the system. Management becomes evenmore crucial for the current trend of multifunction RF systems, as the additional functions place additional demands on the shared resources. Since radar resource management techniques have implemented perception-action cycles for many decades, it is a topic that is very closely related to cognitive radar. In the “Cognitive Radar Architecture” section, a cognitive radar architecture is presented, within which cognitive radar techniques can be realized. Then, in the “Development of Adaptivity in Radar Resource Management” and “Drive to Cognitive Radar Resource Management” sections, an overview of adaptive and cognitive radar resource management techniques is presented. As this series of techniques represents increasing adaptation to information or knowledge, the reader is taken on a walk along the cognitive spectrum in the context of radar resource management. The “Challenges and Drawbacks” section discusses drawbacks and challenges that should be considered in the cognitive radar research and development process.