Research on Radar Target Recognition Algorithms

Radar target recognition is the process of identifying the presence, position, size, type and other attributes of an object using radar echo signals. There are two main approaches for radar target recognition: statistical methods and feature-based methods. Statistical methods rely on techniques such as likelihood ratio test, track before detect and constant false alarm rate to analyze the signal characteristics. Feature-based methods employ machine learning methods such as deep learning to extract and classify the target features. Radar target recognition has various applications in domains such as autonomous driving, air traffic control and military reconnaissance. This article presents a comprehensive survey of the state-of-the-art, challenges, principles, methods and key technologies of radar target recognition, and discusses the future research directions.