基于深度学习的多波段信号融合用于三维 SAR 超分辨率（英文版）

英文标题：Deep Learning-Based Multiband Signal Fusion for 3-D SAR Super-Resolution中文摘要：提出一种深度学习方法 kR-Net，使用混合的双域复值卷积神经网络 (CV-CNN) 融合多频段信号，以实现对复杂目标的高分辨率成像，从而在安全筛查和工业成像领域中具有广阔应用前景。英文摘要：Three-dimensional (3-D) synthetic aperture radar (SAR) is widely used in manysecurity and industrial applications requiring high-resolution imaging ofconcealed or occluded objects. The ability to resolve intricate 3-D targets isessential to the performance of such applications and depends directly onsystem bandwidth. How