Results 151 to 160 of about 11,437 (192)
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Automatic Radar Waveform Recognition
IEEE Journal of Selected Topics in Signal Processing, 2007In this paper, a system for automatically recognizing radar waveforms is introduced. This type of techniques are needed in various spectrum management, surveillance and cognitive radio or radar applications. The intercepted radar signal is classified to eight classes based on the pulse compression waveform: linear frequency modulation (LFM), discrete ...
Jarmo Lundn, Visa Koivunen
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Transferred deep learning based waveform recognition for cognitive passive radar
Signal Processing, 2019Abstract Passive radar capable of recognizing illumination of opportunities can improve the detection performance on account of its functional properties of environment adaptivity. Waveform recognition approaches based on Deep Learning can outperform traditional methods based on hand-crafted feature as shown in recent studies.
Qing Wang +5 more
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Accurate Deep CNN-Based Waveform Recognition for Intelligent Radar Systems
IEEE Communications Letters, 2021Nowadays radar systems have been facing with the disordered electromagnetic spectrum access and utilization in shared spectrum environments with radio communication systems. Numerous waveform recognition methods have been studied with feature engineering and conventional machine learning (ML) for intelligent radar systems, but they are critically ...
Thien Huynh-The +4 more
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Automatic target recognition using waveform diversity in radar sensor networks
Pattern Recognition Letters, 2008In this paper, we perform a number of theoretical studies on constant frequency (CF) pulse waveform design and diversity in radar sensor networks (RSN): (1) the conditions for waveform co-existence, (2) interferences among waveforms in RSN, (3) waveform diversity combining in RSN. As an application example, we apply the waveform design and diversity to
Qilian Liang
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Efficient TFI-Based Depth-Tunable LPI Radar Waveform Recognition Network
IEEE Signal Processing Letters, 2023Xiti Wang, Zhiyong Luo
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Automatic Radar Waveform Recognition Using SVM
Applied Mechanics and Materials, 2012In this paper, a new feature for radar waveform recognition based on the instantaneous frequency is proposed. It is especially utilized for discriminating phase coded signals from other signals. Maximum likelihood estimation (MLE), autocorrelation algorithm, and likelihood ratio test are exploited in the algorithm. In the classification system, support
Hao Gao, Xu Dong Zhang
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Radar Waveform Recognition based on Deep Residual Network
2019 IEEE 8th Joint International Information Technology and Artificial Intelligence Conference (ITAIC), 2019This article presents our initial results in deep learning for the complex multiple radar waveforms recognition. The method is composed of time-frequency analysis and deep residual network (ResNet). Firstly, we transform one-dimensional radar signals into two-dimensional time-frequency images (TFIs), which can reveal more characteristics of the signals.
Xin Qin +3 more
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Relationship of target recognition performance and radar waveform parameters
Journal of Electronics (China), 2011Target recognition performance can be affected by radar waveform parameters. In this paper, we established rigorous relationship between target recognition efficiency and the parameters of a repeatedly transmitted waveform. It is based on Kullback-Leibler Information Number of single observation (KLINs), which measures the dissimilarity between targets
Meimei Fan +4 more
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