Results 131 to 140 of about 31,814 (175)

Radar Emitter Identification Based on Naive Bayesian Algorithm

2020 IEEE 5th Information Technology and Mechatronics Engineering Conference (ITOEC), 2020
The aim of this study is to realize radar emitter Identification with high-efficiency. In this article, an approach based on naive Bayesian algorithm is introduced. For recognizing radar radiations, this paper utilizes Naive Bayes classifier for radar signal sorting, and selects the pulse parameters (direction of arrival, pulse width, pulse repetition ...
Zhiling Xiao, Zhenya Yan
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Radar Emitter Identification based on CNN and FPGA Implementation

2024 IEEE 6th Advanced Information Management, Communicates, Electronic and Automation Control Conference (IMCEC)
Recently, deep learning (DL) models based on convolutional neural networks (CNN) have been used for radar emitter identification (REI). However, CNNs typically have high parameter and computational complexity, posing a challenge to limited computing ...
Jun’an Lu, Jun Hu
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Radar emitter identification based on EPSD-DFN

2018 IEEE 3rd Advanced Information Technology, Electronic and Automation Control Conference (IAEAC), 2018
Aimed at the problem that the radar emitter characteristic parameters are not fully used in the identification process and the stability of the radar parameter of sample map is not stable enough, the estimation parameter sample diagram (EPSD) is used to describe the characteristic parameter description model of the radar radiant source. A radar emitter
Qiu Jin, Hongyan Wang, Kaizhi Yang
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Radar Emitter Identification Based on Deep Convolutional Neural Network

2018 International Conference on Control, Automation and Information Sciences (ICCAIS), 2018
Aiming at the identification and classification of radar radiation sources, this paper proposes a classification method based on the Convolutional Neural Network(CNN) for radar signal classification. Firstly, this paper sets the appropriate learning rate, batch size, iteration number, momentum and weight decay coefficient.
Mingxin Kong, Jing Zhang 0037, Weifeng Liu 0004, Guilin Zhang   +3 more
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MDGAN-TPAMDPN-Net: A Self-Sufficient and Calibrated Network for Radar Emitter Identification

IEEE Internet of Things Journal
This article develops the maximum diversity generative adversarial network (MDGAN)-TPAMDPN-Net for radar emitter identification (REI). 1) The number of training samples in the database is limited in real world, which leads to the inability to effectively
Kun Li, Yunchuan Xue, Haibo Lan
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Enhanced Semi-Supervised Radar Emitter Identification via Virtual Adversarial Training

2024 IEEE 99th Vehicular Technology Conference (VTC2024-Spring)
Radar emitter identification (REI) is a crucial function of electronic radar warfare support systems. The challenge emphasizes identifying and locating unique transmitters, avoiding potential threats, and preparing countermeasures.
Hong Wan, Ziqin Feng, Qianyun Zhang 0001, Yu Wang 0078, Xue Fu, Yun Lin 0005, Fumiyuki Adachi, Guan Gui 0001   +7 more
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Radar Emitter Identification with Bispectrum based LBP and Extreme Learning Machine

2018 IEEE 23rd International Conference on Digital Signal Processing (DSP), 2018
Radar Emitter Identification (REI) has been a long-standing topic in military and civil fields. In this paper, we present a novel REI based on the local binary pattern (LBP) feature extracted from bispectrum of radar signal and the extreme learning machine (LBP+ELM). Comparing with conventional radar features, the high-order spectral analysis method is
Ru Cao, Jiuwen Cao
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Radar emitter identification based on discriminant joint distribution adaptation

2019 IEEE 3rd Advanced Information Management, Communicates, Electronic and Automation Control Conference (IMCEC), 2019
Aiming at the problem that the existing radar emitter identification method cannot effectively identify the radar signal unknown to the prior knowledge base, this paper introduces the joint distribution adaptation algorithm in transfer learning into the field and adds data label to the algorithm optimization item.
Xiaohui Ran, Weigang Zhu
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A comparison study of radar emitter identification based on signal transients

2018 IEEE Radar Conference (RadarConf18), 2018
Radar emitter identification has been studied for decades using library-based techniques that rely on pre-existing knowledge of parameters such as radio frequency (RF), pulse amplitude, pulse width, intentional pulse modulation type, or pulse repetition intervals.
Shanzeng Guo, Robert Edward White, Michael Low   +2 more
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Radar Emitter Identification Based on Improved Convolutional Neural Network

2019 IEEE 3rd Advanced Information Management, Communicates, Electronic and Automation Control Conference (IMCEC), 2019
Aiming at the problem that the traditional pulse description word is difficult to effectively identify complex radar emitters, a method of extracting time-frequency characteristics of radar emitters and using improved convolutional neural network for recognition is proposed.
Kun Li
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