Due to the advantages of Synthetic Aperture Radar (SAR), the study of Automatic Target
Recognition (ATR) has become a hot topic. Deep learning, especially in the case of a …

The proliferation of remote sensing (RS) technologies has remarkably augmented the
volume and 33 fidelity of RS imagery, which is critical and influential for characterizing …

基于深度神经网络的雷达像智能识别技术已经成为雷达信息处理领域的前沿和热点. 然而,
神经网络分类模型易受到对抗攻击的威胁. 攻击者可以在隐蔽的条件下误导智能目标识别模型做 …

Deep neural network (DNN)-based synthetic aperture radar (SAR) automatic target
recognition (ATR) systems have been shown to be highly vulnerable to adversarial …

In recent years, deep learning has been widely used in synthetic aperture radar (SAR)
automatic target recognition (ATR) and achieved excellent performance on the moving and …

This letter proposes a learning aided gradient descent (LAGD) algorithm to solve the
weighted sum rate (WSR) maximization problem for multiple-input single-output (MISO) …

Synthetic aperture radar (SAR), as an active microwave sensor, can inevitably receive radio
frequency interference (RFI) generated by various electromagnetic equipment. When the …

Recent years have witnessed the great success of deep learning algorithms in the
geoscience and remote sensing (RS) realm. Nevertheless, the security and robustness of …

Intelligent radar image recognition based on Deep Neural Networks (DNN) has become an
important topic in radar information processing. However, DNN models are susceptible to …

It has been demonstrated that deep neural network (DNN)-based synthetic aperture radar
(SAR) automatic target recognition (ATR) techniques are extremely susceptible to …