A New Method for Joint Recognition and Location of Radar Jamming
Yafei Song, Ganggang Dong, Zixuan Wang · IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium · 2022
Radar plays an increasingly important role in the civil applications as well as the military ones. Nowadays, various kinds of jamming strategies were presented to blind the radar. It is urgent to identify and recognize those jamming signals in the realistic applications. The early works relied on the predefined handcrafted features. They are highly dependent on the expert knowledge. Likewise, it is difficult to locate the jamming signal accurately. To solve this problem, this paper proposes a new method for joint detection and identification of jamming signals. A backbone composed of some convolutional blocks are presented to learn the high-level features. They are used to locate the jamming signals in the timefrequency plane. The identification of the interfering signal can be then recognized simultaneously. Multiple experiments are performed to demonstrate the effectiveness of proposed method.