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Sparsity-based Time-Frequency Analysis for Automatic Radar Waveform Recognition
2020 IEEE International Radar Conference (RADAR), 2020In this paper, we develop a novel pre-processing algorithm to achieve effective signal denoising for improved recognition of noisy radar signals. The algorithm is considered in the instantaneous autocorrelation function domain in which time or lag slices are converted to a Hankel matrix, and an atomic norm-based method is applied to mitigate the ...
Shuimei Zhang +2 more
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Radar Adaptive Waveform Selection Behavior Recognition Based on Neural Network
2020 IEEE 3rd International Conference on Electronics Technology (ICET), 2020Cognitive radar has the ability to perceive the environment and target information, and complete the work state optimization through analysis and decision. Radar's behavior is defined as all the characteristics of a radar's performance and the process of changing its state according to the law of change and the external influences.
Kaiyuan Zhang +3 more
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Towards an accurate radar waveform recognition algorithm based on dense CNN
Multimedia Tools and Applications, 2020Existing algorithms for radar waveform classification currently exhibit the lower recognition accuracy, especially at the lower signal to noise ratio (SNR) environment. To remedy these flaws, this paper proposes an accurate automatic modulation classification algorithm based on dense convolutional neural networks (AAMC-DCNN).
Weijian Si, Chenxia Wan, Chunjie Zhang
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Radar Signal Waveform Recognition Based on Convolutional Denoising Autoencoder
2019To solve the problem of the low recognition rate of the existing methods at low signal-to-noise ratio (SNR), we propose a novel method of radar signal waveform recognition. In this method, we extract the time-frequency images (TFIs) of radar signals through Cohen class time frequency distribution. Then, we introduce convolutional denoising autoencoder (
Zhaolei Liu, Xiaojie Mao, Zhian Deng
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Automatic Radar Waveform Recognition Based on Deep Convolutional Denoising Auto-encoders
Circuits, Systems, and Signal Processing, 2018Aimed at the deficiency of traditional feature extraction techniques in radar emitter recognition, a novel deep feature extraction and recognition architecture is proposed. To fit into the model, the time-domain emitters are transformed into unique time-frequency images correspondingly.
Zhiwen Zhou +3 more
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Adaptive single-tone waveform design for target recognition in cognitive radar
IET Conference Publications, 2009Cognitive radar is a recently proposed system concept, one of whose most important characteristics is the closed-loop operation. The feedback structure from the receiver to the transmitter enables the optimization of transmission waveforms based on the latest knowledge about targets and environments.
null Yimin Wei +2 more
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Deep Learning for Coexistence Radar-Communication Waveform Recognition
2021 International Conference on Information and Communication Technology Convergence (ICTC), 2021Thien Huynh-The +3 more
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Low Probability of Intercept Radar Waveform Recognition Based on Dictionary Leaming
2018 10th International Conference on Wireless Communications and Signal Processing (WCSP), 2018Low probability of intercept (LPI) radar waveform recognition is a challenging task in modern radar and electronic warfare (EW) systems. To solve the problem of incomplete information and the need for human experience in the existing feature-based radar recognition methods, a robust and automatic LPI radar waveform recognition method based on Choi ...
Huan Wang, Ming Diao, Lipeng Gao
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Use of wideband waveforms for target recognition with surveillance radars
Record of the IEEE 2000 International Radar Conference [Cat. No. 00CH37037], 2002A long range target recognition system has been developed using a high range resolution mode in a surveillance radar. The radar performs normal air surveillance but on targets of interest a wideband waveform is used in a few pulses of the normal dwell. These pulses are processed to yield high resolution range profiles of the target.
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Automatic LPI Radar Waveform Recognition Using Vision Transformer
2023 IEEE International Radar Conference (RADAR), 2023Junseob Kim +3 more
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