Results 11 to 20 of about 1,458 (182)
Micro-Doppler radar deception and camouflage of airborne targets. [PDF]
Sci RepMicro-Doppler signatures are ubiquitous in radar-based object recognition and classification, as they contain information about the internal structure of observed targets. While modern machine learning algorithms achieve unprecedented accuracy in target classification, they are susceptible to deceptive manipulation by introducing intelligent artificial
Kozlov V +6 more
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Micro-Doppler based Target Recognition with Radars: A Review [PDF]
IEEE Sensors Journal, 2021 This is a review article discussing the progress in using micro-doppler based features for target classification.
Ali Hanif +3 more
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Dop‐NET: a micro‐Doppler radar data challenge [PDF]
Electronics Letters, 2020 Radar sensors have a new growing application area of dynamic hand gesture recognition. Traditionally radar systems are considered to be very large, complex and focused on detecting targets at long ranges. With modern electronics and signal processing it is now possible to create small compact RF sensors that can sense subtle movements over short ranges.
M. Ritchie, R. Capraru, F. Fioranelli
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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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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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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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Micro-Doppler Feature Extraction of Rotating Structures of Aircraft Targets with Terahertz Radar
Remote Sensing, 2022 The micro-Doppler features formed by the micro-motion of rotating blades of rotors and turbines are of great significance for aircraft target detection and recognition.
Xiaoyu Qin, Bin Deng, Hongqiang Wang
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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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Leida xuebao, 2018 In this paper, experimental results of micro-Doppler effect on a multi-rotor drone with digital television based passive radar are discussed. First, the bistatic passive radar micro-motion model of the drone is established.
Liu Yuqi +5 more
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