Results 11 to 20 of about 1,336 (197)
IET Radar, Sonar & Navigation, 2023 This study proposes a small sample recognition method for radar waveforms based on data enhancement of ambiguity function generative adversarial networks (AFGAN) to address the issue of low recognition rate and unbalanced class recognition rate.
Haijun Wang +7 more
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LPI Radar Waveform Recognition Based on CNN and TPOT [PDF]
Symmetry, 2019 The electronic reconnaissance system is the operational guarantee and premise of electronic warfare. It is an important tool for intercepting radar signals and providing intelligence support for sensing the battlefield situation. In this paper, a radar waveform automatic identification system for detecting, tracking and locating low probability ...
Jian Wan, Xin Yu, Qiang Guo
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Extended Target Recognition in Cognitive Radar Networks
Sensors, 2010 We address the problem of adaptive waveform design for extended target recognition in cognitive radar networks. A closed-loop active target recognition radar system is extended to the case of a centralized cognitive radar network, in which a generalized ...
Xiqin Wang +3 more
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Radar Waveform Recognition Using Fourier-Based Synchrosqueezing Transform and CNN [PDF]
2019 IEEE 8th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), 2019 In this paper the problem of recognizing radar waveforms is addressed. Waveform classification is needed in spectrum sharing and radar-communications coexistence, cognitive radars and signal intelligence. Different radar waveforms exhibit different properties in time-frequency domain. We propose a deep learning method for waveform classification.
Koivunen, Visa, Kong, Gyuyeol
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Radar Operation Mode Recognition via Multifeature Residual-and-Shrinkage ConvNet
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2023 Radar operation mode recognition holds an increasingly critical place in electronic countermeasure as well as in remote sensing. However, the overlapped waveform parameters pose huge challenges to performing the radar operation mode recognition task in ...
Yujie Zhang +6 more
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Densely-Accumulated Convolutional Network for Accurate LPI Radar Waveform Recognition
2021 IEEE Global Communications Conference (GLOBECOM), 2021 Abstract This paper presents a deep learning-based method to automatically recognize low probability of intercept (LPI) radar waveforms against diversified jamming attacks. Concretely, an efficient convolutional neural network (CNN) architecture, namely Densely-Accumulated Network (DANet), is introduced to learn the time-frequency representation ...
Thien Huynh-The +6 more
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LPI Radar Waveform Recognition Based on Hierarchical Classification Approach and Maximum Likelihood Estimation [PDF]
EntropyThe importance of information gathering is emphasized to minimize casualties and economic losses in warfare. Through electronic warfare, which utilizes electromagnetic waves, it is possible to discern the enemy’s intentions and respond accordingly ...
Kiwon Rhee +3 more
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EURASIP Journal on Wireless Communications and Networking, 2007 Automatic target recognition (ATR) in target search phase is very challenging because the target range and mobility are not yet perfectly known, which results in delay-Doppler uncertainty.
Qilian Liang
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Automatic LPI radar waveform recognition of overlapping signals based on vision language model [PDF]
Scientific ReportsLow probability of intercept (LPI) microwave waveforms are commonly utilized in multiple radar systems. Identifying precisely the modulation formats of LPI waveform is of importance in complex electromagnetic environment.
Pengkun Yang +4 more
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Sensors, 2022 This article aims to propose an algorithm for the automatic recognition of selected radar signals. The algorithm can find application in areas such as Electronic Warfare (EW), where automatic recognition of the type of intra-pulse modulation or the type ...
Marta Walenczykowska, Adam Kawalec
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