In recent years, the performances of radar resolution, coverage, and detection accuracy
have been significantly improved through the use of ultra-wideband, synthetic aperture and …

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 …

A comprehensive and well-structured review on the application of deep learning (DL) based
algorithms, such as convolutional neural networks (CNN) and long-short term memory …

The range resolution of high-resolution wideband radar is much smaller than the target size.
Its echo signals tend to be diverse and sensitive to small changes of targets. Therefore, it is …

Aflatoxin is commonly exists in moldy foods, it is classified as a class one carcinogen by the
World Health Organization. In this paper, we used one dimensional convolution neural …

Robust and efficient feature extraction is critical for high-resolution range profile (HRRP)-
based radar automatic target recognition (RATR). In order to explore the correlation between …

In remote sensing, micro-Doppler signatures are widely used in moving target detection and
automatic target recognition. However, since Doppler signatures are easily affected by the …

In this paper, a target-attentional convolutional neural network (TACNN) combining the
convolutional neural network (CNN) and attention mechanism is proposed for radar high …

In this paper, we develop a Target-Aware Recurrent Attentional Network (TARAN) for Radar
Automatic Target Recognition (RATR) based on High-Resolution Range Profile (HRRP) to …

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