Results 21 to 30 of about 564 (134)
Radar signal recognition exploiting information geometry and support vector machine
IET Signal Processing, 2023 Aiming at the recognition of low‐probability‐of‐intercept (LPI) radar signals, a support vector machine (SVM)‐based algorithm is proposed, where the information geometry theory is utilised to optimise the kernel function of the SVM.
Yuqing Cheng, Muran Guo, Limin Guo
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Radar signal recognition based on triplet convolutional neural network
EURASIP Journal on Advances in Signal Processing, 2021 Recently, due to the wide application of low probability of intercept (LPI) radar, lots of recognition approaches about LPI radar signal modulations have been proposed.
Lutao Liu, Xinyu Li
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LPI Radar Waveform Recognition Based on Multi-Resolution Deep Feature Fusion
IEEE Access, 2021 Deep neural networks are used as effective methods for the Low Probability of Intercept (LPI) radar waveform recognition. However, existing models' performance degrades seriously at low Signal-to-Noise Ratios (SNRs) because the effective features ...
Xue Ni +4 more
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Sensors, 2020 Radar network systems have been demonstrated to offer numerous advantages for target tracking. In this paper, a low probability of intercept (LPI)-based joint dwell time and bandwidth optimization strategy is proposed for multi-target tracking in a radar
Lintao Ding +3 more
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IEEE Open Journal of the Communications Society, 2023 To achieve low probability of intercept (LPI) in radar networks for multiple target detection, it is necessary to find the optimal assignment of distributed radars to targets.
Hamid Amiriara +2 more
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Densely-Accumulated Convolutional Network for Accurate LPI Radar Waveform Recognition [PDF]
, 2022 This paper presents a deep learning-based method to automatically recognize low probability of intercept (LPI) radar waveforms against diversified jamming attacks.
Kim, Dong-Seong +6 more
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LPI Radar Waveform Recognition Based on Neural Architecture Search [PDF]
Computational Intelligence and Neuroscience, 2022 In order to reach the intelligent recognition, the deep learning classifiers adopted by radar waveform are normally trained with transfer learning, where the pretrained convolutional neural network on an external large-scale classification dataset (e.g., ImageNet) is used as the backbone.
Zhiyuan Ma 0004 +5 more
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IET Radar, Sonar & Navigation, 2021 This paper proposes a collaborative transmit resource scheduling and waveform selection (CTRSWS) strategy for target tracking in multistatic radar system which consists of one transmitter and an arbitrary number of receivers.
Yijie Wang +3 more
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Remote Sensing, 2023 This paper studies a coalition game theoretic power allocation algorithm for multi-target detection in radar networks based on low probability of intercept (LPI).
Xiangrong Dai +3 more
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Sensors, 2023 In the process of using the Distributed Radar Network Localization System (DRNLS) further to improve the survivability of a carrier platform, the random characteristics of the system’s Aperture Resource Allocation (ARA) and Radar Cross Section (RCS) are ...
Chenyan Xue, Ling Wang, Daiyin Zhu
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