The purpose of this paper is to survey and assess the state-of-the-art in automatic target
recognition for synthetic aperture radar imagery (SAR-ATR). The aim is not to develop an …

It is a feasible and promising way to utilize deep neural networks to learn and extract
valuable features from synthetic aperture radar (SAR) images for SAR automatic target …

It is well-known that the convolutional neural network (CNN) is an effective method for
synthetic aperture radar (SAR) target classification. In the convolutional layer of CNN …

The state-of-the-art deep neural networks have made a great breakthrough in remote
sensing image classification. However, the heavy dependence on large-scale data sets …

Recent years have witnessed a remarkable breakthrough in synthetic aperture radar
automatic target recognition (SAR ATR) with the development of deep learning (DL) …

The convolutional neural network (CNN) is widely used in synthetic aperture radar (SAR)
target recognition, but conventional CNN mainly adopts a single-scale convolutional kernel …

In recent years, synthetic aperture radar (SAR) automatic target recognition (ATR) has been
widely used in both military and civilian fields. Due to the sensitivity of SAR images to the …

自动目标识别(ATR) 是一个和信号与信息处理, 模式识别, 人工智能等学科密切相关的特殊工程
技术应用领域. 由于ATR 系统识别对象固有的不确定性, 识别环境的复杂性 …

Automatic target recognition (ATR) in synthetic aperture radar (SAR) images has been
widely used in civilian and military fields. Traditional model-based methods and template …

With the recent advances of deep learning, automatic target recognition (ATR) of synthetic
aperture radar (SAR) has achieved superior performance. By not being limited to the target …