Zobrazeno 1 - 10
of 42
pro vyhledávání: '"Daegun Oh"'
Publikováno v:
IEEE Access, Vol 9, Pp 46422-46429 (2021)
In this paper, we propose to produce synthesized micro-Doppler signatures from different aspect angles through conditional generative adversarial networks (cGANs). Micro-Doppler signatures of non-rigid human body motions vary considerably as a functi
Externí odkaz:
https://doaj.org/article/de66d57dc0b9472fb5abcaf7330c5c23
Publikováno v:
Sensors, Vol 18, Iss 12, p 4171 (2018)
In this work, a 24-GHz frequency-modulated continuous-wave (FMCW) radar system with two sectoral horn antennas and one transmitting lens antenna for long-range drone detection is presented. The present work demonstrates the detection of a quadcopter-
Externí odkaz:
https://doaj.org/article/b6368b78f6c04725b07ad19a35262572
Publikováno v:
Sensors, Vol 18, Iss 4, p 1113 (2018)
In this paper, a three-dimensional (3D)-subspace-based azimuth angle, elevation angle, and range estimation method with auto-pairing is proposed for frequency-modulated continuous waveform (FMCW) radar with an L-shaped array. The proposed method is d
Externí odkaz:
https://doaj.org/article/e182ebfaa56c4d19abbff697bf5f5312
Publikováno v:
Sensors, Vol 18, Iss 1, p 311 (2018)
This article deals with the development of a dual channel S-Band frequency-modulated continuous wave (FMCW) system for a through-the-wall imaging (TWRI) system. Most existing TWRI systems using FMCW were developed for synthetic aperture radar (SAR) w
Externí odkaz:
https://doaj.org/article/e656c2db784249409c93d58d3a0044e0
Publikováno v:
2022 IEEE 5th International Conference on Electronic Information and Communication Technology (ICEICT).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7146a3a6de2ea709532d997e0224ff3b
https://doi.org/10.1109/iceict55736.2022.9909231
https://doi.org/10.1109/iceict55736.2022.9909231
Publikováno v:
IEEE Sensors Journal. 21:13522-13529
We investigate the feasibility of classifying human activities measured by a MIMO radar in the form of a point cloud. If a human subject is measured by a radar system that has a very high angular azimuth and elevation resolution, scatterers from the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8d97495667fea639a80190ef0deae43c
https://doi.org/10.1109/jsen.2021.3068388
https://doi.org/10.1109/jsen.2021.3068388
Publikováno v:
IEEE Geoscience and Remote Sensing Letters. 17:396-400
We propose using generative adversarial networks (GANs) for the classification of micro-Doppler signatures measured by the radar. Despite Deep Convolutional Neural Networks (DCNNs) having been used extensively in radar image classification in recent
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::22d6ca0cfc63a6d72e91a4c02d30320a
https://doi.org/10.1109/lgrs.2019.2919770
https://doi.org/10.1109/lgrs.2019.2919770
Publikováno v:
IEEE Sensors Journal. 19:4571-4576
We investigated the feasibility of using Doppler radar to recognize human voices by capturing the micro-Doppler signatures of vibrations from the larynx and mouth. The signatures produced through the vibrations of a human being’s vocal cords genera
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bf5e73e82d26e6567855ac0f6b9762c1
https://doi.org/10.1109/jsen.2019.2901271
https://doi.org/10.1109/jsen.2019.2901271
Publikováno v:
Microwave and Optical Technology Letters. 60:2949-2954
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c72ffd971ea55f8e9101923611578647
https://doi.org/10.1002/mop.31408
https://doi.org/10.1002/mop.31408
Publikováno v:
IGARSS
Collecting a large amount of data for radar requires a significant amount of time, labor, and money. In deep convolutional neural networks, a small dataset causes the problem of overfitting. We herein introduce the employment of data augmentation usi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c2d36054fa12b8119c7a658dc83de2db
https://doi.org/10.1109/igarss.2019.8898073
https://doi.org/10.1109/igarss.2019.8898073