Nonhomogeneous Sea Clutter Suppression Using Complex-Valued U-Net Model
Yumiao Wang, Wenjing Zhao, Xiang Wang, Jiahui Chen, Huquan Li, Guolong Cui
Abstract
This letter considers the problem of the target detection in the nonhomogeneous sea clutter environment, and proposes the complex-valued U-Net based clutter suppression method. Specifically, firstly, the complex signal features of radar echo sequences are extracted by developing the complex-valued convolutional blocks. Secondly, the complex multi-level features are fused, by employing the up-down sampling structure and skip connections, to suppress nonhomogeneous sea clutter. Further, the false alarm controllable detector is designed to detect the targets. Finally, the performance of the proposed method is evaluated via real data. The results show that it has a higher detection probability compared with the real-valued U-Net.