Distributed Radar Angle Measurement Based on Deep Learning

Distributed radar systems are pivotal in modern military and civilian contexts, with phased array radar technology greatly impacting angle measurement precision for target tracking and identification. This article presents a novel angle measurement approach for distributed radar systems, harnessing deep learning. This technique not only heightens angle measurement precision but also optimizes network efficiency, enhancing overall system performance. To validate our method, we conducted extensive experiments involving diverse angle targets, both large and small, consistently achieving outstanding results across scenarios. This underscores the method's exceptional accuracy and robustness in real-world situations. In summary, our innovative distributed radar angle measurement technique, driven by deep learning, promises improved accuracy and efficiency, bolstering the capabilities of distributed radar systems across applications.