雷达辐射源信号分选是雷达信号侦察的关键技术之一, 同时也是战场态势感知的重要环节.
该文系统梳理了雷达辐射源信号分选的主流技术, 从基于脉间调制特征, 基于脉内调制特征 …

Radar emitter signal deinterleaving is a key technology for radar signal reconnaissance and
an essential part of battlefield situational awareness. This paper systematically sorts out the …

Classifiers based on machine learning are usually trained to distinguish between several
known classes. For an electronic intelligence application, however, it is of great importance …

Efficient and effective radar emitter recognition is critical for electronic support measurement
(ESM) systems. However, in complex electromagnetic environments, intercepted pulse …

Traditional radar signal sorting (RSS) methods assume that all types of radar signals can be
stored and trained offline. However, the presence of noncooperative radar emitters makes …

Radar emitter identification (REI) aims to extract the fingerprint of an emitter and determine
the individual to which it belongs. Although many methods have used deep neural networks …

In this paper, we compare Markov chains and Long Short-Term Memory neural networks for
the prediction of radar emissions and the identification of the radar's type. This comparison is …

In this paper, we present a method for the identification of different multifunction radar emitter
types. It is based on Long Short-Term Memory recurrent neural networks and a previously …

Deep learning has brought great development to radar emitter identification technology. In
addition, specific emitter identification (SEI), as a branch of radar emitter identification, has …

Recent advancements in radar technology and telecommunications have led to a high
population of increasingly complex emitters in the electromagnetic spectrum. From the …