Radar is one of the core sensors in avionics systems. Over the past few decades, Artificial Intelligence (AI) has undergone significant advancements, revolutionizing traditional theoretical frameworks and enabling new applications, and aligns with the evolving demand for radar signal processing. This paper systematically reviews recent progress in AI-facilitated radar signal processing, from algorithms to hardware supports. First, we give a brief review of radar technology development and fundamental AI methodologies. Then, a comprehensive discussion about how AI enhances critical radar functionalities is presented, including waveform design, target detection, recognition and tracking, clutter and jamming suppression, and imaging. Especially, we overview the hardware architecture selection and optimization methodologies for AI-acceleration processing. Furthermore, emerging applications of intelligent radar are highlighted, spanning from health care to transportation. Practical limitations also exist in deploying AI within radar systems and have been summarized subsequently. Finally, we outline promising directions for future research. This review aims to provide a valuable reference for researchers seeking a clear, structured overview of the state-of-the-art intelligent signal processing techniques for radar systems including, but not limited to the airborne radar.
Li et al. (Wed,) studied this question.