Results 11 to 20 of about 1,468 (180)
IEEE Access, 2021 In this paper, we propose to produce synthesized micro-Doppler signatures from different aspect angles through conditional generative adversarial networks (cGANs).
Ibrahim Alnujaim +3 more
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Robustness of Deep Neural Networks for Micro-Doppler Radar Classification [PDF]
2022 23rd International Radar Symposium (IRS), 2022 With the great capabilities of deep classifiers for radar data processing come the risks of learning dataset-specific features that do not generalize well. In this work, the robustness of two deep convolutional architectures, trained and tested on the same data, is evaluated.
Czerkawski, Mikolaj +4 more
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Radar Measurement of Human Polarimetric Micro-Doppler [PDF]
Journal of Electrical and Computer Engineering, 2013 We use polarimetric micro-Doppler for the detection of arm motion, especially for the classification of whether someone has their arms swinging and is thus unloaded. The arm is often bent at the elbow, providing a surface somewhat similar to a dihedral. This is distinct from the more planar surfaces of the body which allows us to isolate the signals of
David Tahmoush, Jerry Silvious
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Leida xuebao, 2023 Compared with traditional Electromagnetic (EM) wave radars, vortex EM wave radars can simultaneously observe the micro-motion components projected onto the radar’s radial and perpendicular planes, providing more information for target recognition.
Hang YUAN +4 more
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Exploring Radar Micro-Doppler Signatures for Recognition of Drone Types
Drones, 2023 In this study, we examine the use of micro-Doppler signals produced by different blades (i.e., puller and lifting blades) to aid in radar-based target recognition of small drones.
Jun Yan +4 more
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A Deep-Learning Method for Radar Micro-Doppler Spectrogram Restoration [PDF]
Sensors, 2020 Radio frequency interference, which makes it difficult to produce high-quality radar spectrograms, is a major issue for micro-Doppler-based human activity recognition (HAR). In this paper, we propose a deep-learning-based method to detect and cut out the interference in spectrograms. Then, we restore the spectrograms in the cut-out region.
Yuan He 0009 +4 more
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Micro‐motion parameter extraction of rotating target based on vortex electromagnetic wave radar
IET Radar, Sonar & Navigation, 2021 The vortex electromagnetic (EM) wave radar has the potential to obtain more accurate micro‐motion parameters for target recognition. However, with the existing algorithms of micro‐motion parameter extraction it is difficult to obtain the real rotation ...
Hang Yuan +4 more
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International Journal of Advanced Robotic Systems, 2021 The study investigated object detection and classification based on both Doppler radar spectrograms and vision images using two deep convolutional neural networks.
Jnana Sai Abhishek Varma Gokaraju +3 more
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Applied Sciences, 2019 Under the same principle, laser radar could be more sensitive to the micro-Doppler (m-D) effect due to its wave length, as the characteristic of multi-resolution, S transform could reduce the influence of the micro-Doppler component and enhance the ...
Bo Zang +4 more
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ERUO: a spectral processing routine for the Micro Rain Radar PRO (MRR-PRO) [PDF]
Atmospheric Measurement Techniques, 2022 The Micro Rain Radar PRO (MRR-PRO) is a K-band Doppler weather radar, using frequency-modulated continuous-wave (FMCW) signals, developed by Metek Meteorologische Messtechnik GmbH (Metek) as a successor to the MRR-2.
A. Ferrone +2 more
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