Automatic target recognition (ATR) for military applications is one of the core processes
toward enhancing intelligence and autonomously operating military platforms. Spurred by …

Improving ship classification performance in synthetic aperture radar (SAR) imagery by the
methods based on transfer learning (TL) is a newly emerging research topic and has great …

We present advanced Deep Learning (DL) techniques for robust Synthetic Aperture Radar
(SAR) automatic target recognition (ATR) in the presence of noise and signal phase errors …

This work proposes a new Light Detection and Ranging (LIDAR) based navigation
architecture that is appropriate for uncooperative relative robotic space navigation …

Synthetic aperture radar (SAR) images have limited labeled samples, and thus, it is difficult
to learn a perfect convolutional neural network (CNN) model for target classification. The …

Owing to the inherent characteristics of synthetic aperture radar (SAR) imaging system
based on the coherent imaging modality, SAR images are inevitably corrupted by speckle …

With the advent of the artificial intelligence era, target adaptive tracking technology has been
rapidly developed in the fields of human‐computer interaction, intelligent monitoring, and …

Recognition and Identification of targets are crucial steps in the radar signal processing
chain. Due to their high resolution, imaging radars are a well suitable choice for these tasks …

The contour thinning algorithm is an imaging algorithm for circular synthetic aperture radar
(SAR) that can obtain clear target contours and has been successfully used for circular SAR …

A synthetic aperture radar (SAR) target classification method is proposed by selecting deep
features learned by convolutional neural network (CNN) using the nonlinear correlation …