Results 21 to 30 of about 926 (278)

1D-CNN-Transformer for Radar Emitter Identification and Implemented on FPGA

Remote Sensing
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 also benefited from it.
Xiangang Gao, Bin Wu, Peng Li, Zehuan Jing   +3 more
doaj   +2 more sources

Radar Emitter Recognition Based on the Energy Cumulant of Short Time Fourier Transform and Reinforced Deep Belief Network

Sensors, 2018
To cope with the complex electromagnetic environment and varied signal styles, a novel method based on the energy cumulant of short time Fourier transform and reinforced deep belief network is proposed to gain a higher correct recognition rate for radar ...
Xuebao Wang, Gaoming Huang, Zhiwen Zhou, Wei Tian, Jialun Yao, Jun Gao   +5 more
doaj   +2 more sources

Towards Single-Component and Dual-Component Radar Emitter Signal Intra-Pulse Modulation Classification Based on Convolutional Neural Network and Transformer

Remote Sensing, 2022
In the modern electromagnetic environment, the intra-pulse modulations of radar emitter signals have become more complex. Except for the single-component radar signals, dual-component radar signals have been widely used in the current radar systems.
Shibo Yuan, Peng Li, Bin Wu
doaj   +2 more sources

IRelNet: An Improved Relation Network for Few-Shot Radar Emitter Identification

Drones, 2023
In future electronic warfare (EW), there will be many unmanned aerial vehicles (UAVs) equipped with electronic support measure (ESM) systems, which will often encounter the challenge of radar emitter identification (REI) with few labeled samples.
Zilong Wu, Meng Du, Daping Bi, Jifei Pan
doaj   +2 more sources

A Denoising Method Based on DDPM for Radar Emitter Signal Intra-Pulse Modulation Classification

Remote Sensing
Accurately classifying the intra-pulse modulations of radar emitter signals is important for radar systems and can provide necessary information for relevant military command strategy and decision making.
Shibo Yuan, Peng Li, Xu Zhou, Yingchao Chen, Bin Wu   +4 more
doaj   +2 more sources

Deep Muti-Modal Generic Representation Auxiliary Learning Networks for End-to-End Radar Emitter Classification

Aerospace, 2022
Radar data mining is the key module for signal analysis, where patterns hidden inside of signals are gradually available in the learning process and its superiority is significant for enhancing the security of the radar emitter classification (REC ...
Zhigang Zhu, Zhijian Yi, Shiyao Li, Lin Li   +3 more
doaj   +2 more sources

MULTISTATIC RADAR EMITTER IDENTIFICATION USING ENTROPY MAXIMIZATION BASED INDEPENDENT COMPONENT ANALYSIS [PDF]

Journal of Engineering Science and Technology, 2018
Radar emitter identification is state-of-the-art in modern electronic warfare. Presently multistatic architecture is adapted by almost all the radar systems for better tracking performance and accuracy in target detection.
DILLIP DASH, VALARMATHI J.
doaj   +2 more sources

Dual‐labelled multi‐Bernoulli filter based on specific emitter identification

IET Radar, Sonar & Navigation
In complex electromagnetic environments, airborne passive bistatic radar encounters the challenge of associating emitters with measurements for multi‐target tracking.
Xin Guan, Yu Lu
doaj   +2 more sources

A Unified Method for Deinterleaving and PRI Modulation Recognition of Radar Pulses Based on Deep Neural Networks

IEEE Access, 2021
In the modern electronic warfare signal environment, multiple radar signals of high density are mixed and received, and separating them into signals for each emitter is an essential step for emitter identification. Each radar has its own pulse repetition
Jin-Woo Han, Cheong Hee Park
doaj   +1 more source

Blind Source Separation of Radar Signals in Time Domain Using Deep Learning

, 2023
486491Identification and further analysis of radar emitters in a contested environment requires detection and separation of incoming signals. If they arrive from the same direction and at similar frequencies, deinterleaving them remains challenging.
Hinderer, Sven
core   +1 more source