Results 71 to 80 of about 750 (192)

Robust LPI Radar Signal Recognition via SNR‐Guided Generative Restoration and Active Recurrent Glance‐and‐Focus

IET Radar, Sonar &Navigation, Volume 20, Issue 1, January/December 2026.
To address the challenge of low probability of intercept (LPI) radar signal recognition under low SNR conditions, this paper proposes a unified framework integrating SNR‐guided generative restoration with an active recurrent glance‐and‐focus classification strategy. By leveraging an RA‐UnetJiT restoration network and a deep reinforcement learning agent,
Yu Cheng, Jiantao Wang, Jie Huang, Yiming Li, Dexiu Hu   +4 more
wiley   +1 more source

LPI Radar Signal Recognition Using Deep-learning Neural Network

, 2021
Currently, radar equipment uses Low Probability Intercepted (LPI) signals. Meanwhile, modulated radar signal is one of the important information in electronic reconnaissance, allowing the identification of the emission source.
Nguyễn Văn Linh, Đoàn Văn Sáng, Trần Công Tráng, Trần Văn Cường
core  

Single‐Channel Multi‐Component Linear Frequency Modulation Signal Blind Separation Based on Multi‐Feature Enhanced Swin‐Transformer

IET Radar, Sonar &Navigation, Volume 20, Issue 1, January/December 2026.
To address the underdetermined blind source separation problem of single‐channel multi‐component linear frequency modulation (LFM) signals, the separation task is reformulated as a semantic segmentation problem on time‐frequency spectrograms. A multi‐feature enhanced Swin‐Transformer network, integrating an optimised convolutional block attention ...
Weifeng Sun, Xinyue Wang, Chao Zhang, Peng Zhang, Qi Liu   +4 more
wiley   +1 more source

Parameteruppskattning av LPI radar i brusiga miljöer med faltningsnätverk

, 2021
Low-probability-of-intercept (LPI) radars are notoriously difficult for electronic support receivers to detect and identify due to their changing radar parameters and low power.
Appelgren, Filip
core  

Research on Amplitude Characteristics of FDA‐AWACS and Direction Finding Mechanism of Anti‐Beam Search Method

IET Radar, Sonar &Navigation, Volume 20, Issue 1, January/December 2026.
This paper addresses the poor survivability of AWACS against passive positioning in electromagnetic countermeasures by investigating the amplitude–frequency response and antibeam search direction‐finding deception mechanism of FDA‐based AWACS, with the goal of offering theoretical support and technical solutions for antipassive direction finding.
Jing Zhang, Bo Wang, Haowei Zhang
wiley   +1 more source

Identification of Radar Emitters Using Radar Signal Sound and Transfer Learning Deep Convolutional Neural Networks

IET Radar, Sonar &Navigation, Volume 20, Issue 1, January/December 2026.
This study introduces a novel approach for identifying threat radars using radar signal sound and transfer learning with six pre‐trained DCNNs. Trained on real ELINT data from 10 radar classes, VGG16 achieved 96.74% accuracy with 11.15s training time, whereas ResNet50V2 achieved 97.83% accuracy. ABSTRACT Identifying threat radars is one of the critical
Sadegh Nezarat, Azar Mahmoodzadeh, Hamed Agahi, Zahra Maghsoodzadeh Sarvestani   +3 more
wiley   +1 more source

Automatic LPI Radar Signal Sensing Method Using Visibility Graphs

IEEE Access, 2020
The issue of the low probability of intercept (LPI) radar signal sensing has received considerable attention. Furthermore, the development of military technology further increased demand for it in future electronic warfare (EW).
Tao Wan, Kaili Jiang, Yanli Tang, Ying Xiong, Bin Tang   +4 more
doaj   +1 more source

Low‐Probability‐Of‐Intercept Point Beam Design for Frequency Diverse Array‐Multiple‐Input Multiple‐Output Radio Detectors Based on Adaptive Weight‐Deep Deterministic Policy Gradient Reinforcement Learning

IET Radar, Sonar &Navigation, Volume 20, Issue 1, January/December 2026.
This study focuses on the design of low‐probability‐of‐intercept (LPI) point beams for the radio detector. We construct a new evaluation model to verify the spatial LPI performance. Frequency diverse array‐multiple‐input multiple‐output (FDA‐MIMO) beams are employed and key factors influencing beam convergence are determined.
Jinwei Jia, Min Gao, Yuying Liang, Yuanwei Yin, Zhuangzhi Han   +4 more
wiley   +1 more source

Adapting Image‐Based Models for 1D Data via Spider Plot Transformation and Transfer Learning

Advanced Intelligent Systems, Volume 7, Issue 12, December 2025.
A novel method enables the use of pretrained image‐based neural networks for complex 1D data, including Raman and mid‐infrared spectra, electrocardiograms, and mass spectrometry. 2D spider plots with false‐color fill enable transfer lerning, therefore enhancing data augmentation and model explainability across diverse spectral and time series datasets.
Azadeh Mokari, Oleg Ryabchykov, Thomas Bocklitz   +2 more
wiley   +1 more source

Interception of Continuous-Emission Noise Radars Transmitting Different Waveform Configurations

, 2022
The literature on Noise Radar Technology (NRT) highlights its features against intercept receivers in terms of low probability of intercept (LPI) as well as of exploitation (LPE).
Pavan, Gabriele, Galati, Gaspare, Wasserzier, Christoph   +2 more
core   +1 more source