Recently, the deep learning models have achieved great success in the recognition of
inverse synthetic aperture radar (ISAR) images. However, most of the deep learning models …

Warhead and decoy classification is one of the most important and difficult technical
problems in ballistic missile defence. The conventional methods extract features from the …

Since the radar imaging can serve as an ill-posed inverse problem, it is an appealing topic
to introduce deep learning instead of regularized iterative algorithm to address the presence …

In modern warfare, the defense of ballistic missile is an important task of air defense
warning, and radar-based target recognition is the core of defense. In this paper, the …

The radar cross section (RCS) is an important parameter that reflects the scattering
characteristics of radar targets. Based on the monostatic radar RCS time series' statistical …

Modern radar systems are expected not only to indicate the presence of an object but also to
provide Automatic Target Recognition and Non-Cooperative Target Recognition. It seems …

We propose a method to recognize and classify inverse synthetic-aperture radar (ISAR)
images of a target. The information that is combined from various image frames, it is …

This paper proposes a dechirping multiplication modulation jamming method for countering
ISAR. The wideband linear frequency modulation (LFM) signal is converted into a single …

In this paper, the main objective is to detect changes in the geographical area of Ottawa city
in Canada due to floods. Two multi-temporal Synthetic Aperture Radar (SAR) images have …

Because of the low accuracy of fuzzy image target recognition, an algorithm of fuzzy image
target recognition based on visual similarity was researched. First, the method of adaptive …