Radar automatic target recognition (RATR) technology is fundamental but complicated
system engineering that combines sensor, target, environment, and signal processing …

Radar target detection (RTD) is a fundamental but important process of the radar system,
which is designed to differentiate and measure targets from a complex background. Deep …

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 …

In this paper, a deep neural network with concatenated structure is created for the
recognition of flight targets. Compared with the traditional recognition method, the deep …

Radar target recognition via deep learning has been an active research area recently.
However, this family of methods depends on the quality of radar images and the number of …

Feature extraction is the key technique for radar automatic target recognition (RATR) based
on high-resolution range profile (HRRP). Traditional feature extraction algorithms usually …

For target detection tasks in complicated backgrounds, a deep learning-based radar target
detection method is suggested to address the problems of a high false alarm rate and the …

Abstract Automatic Target Recognition (ATR) is an important research area in the field of
radar information processing. Because the deep Convolution Neural Network (CNN) does …

In radar high-resolution range profile (HRRP)-based target recognition, one of the most
challenging tasks is the noncooperative target recognition with imbalanced training data set …

For predictive analysis and automatic classification, Deep Neural Networks (DNNs) are
investigated and visualized. All the DNNs used for Automatic Target Recognition (ATR) have …