Zobrazeno 1 - 10
of 33
pro vyhledávání: '"Bokun Tian"'
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 13, Pp 4476-4492 (2020)
Since the compressed sensing (CS) theory broke through the limitation of the traditional Nyquist sampling theory, it has attracted extensive attention in the field of microwave imaging. However, in 3-D microwave sparse reconstruction application, con
Externí odkaz:
https://doaj.org/article/f040fbc1959c49c1952445abe4ca6f51
Publikováno v:
IEEE Access, Vol 7, Pp 179842-179863 (2019)
The environmental interference and the noise in 3D synthetic aperture radar (SAR) image, considered as the background, are inescapable and ought to be eliminated. For 3D SAR image, there is a spatial separation of the target and the background. There
Externí odkaz:
https://doaj.org/article/8d5078026f7943e0b33eb56b25c00bdc
Publikováno v:
IEEE Access, Vol 7, Pp 178710-178725 (2019)
Compressed sensing (CS) algorithms are used for linear array synthetic aperture radar (LASAR) three-dimensional (3D) imaging. However, it is difficult to obtain imaging results with both high computational efficiency and promising imaging quality. Be
Externí odkaz:
https://doaj.org/article/2f73437aa0354906867c9a4203ae814a
Publikováno v:
International Journal of Remote Sensing. 44:78-104
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e364b9a45c9f4761b5c1fd459bf5d075
https://doi.org/10.1080/01431161.2022.2157685
https://doi.org/10.1080/01431161.2022.2157685
Publikováno v:
Remote Sensing Letters. 14:80-90
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::28d0c445dfe74aec36c1f8b6d55a84dd
https://doi.org/10.1080/2150704x.2022.2161847
https://doi.org/10.1080/2150704x.2022.2161847
Autor:
Chen Wang, Jun Shi, Chongben Tao, FengLei Xu, Xinxin Tang, Liang Li, Yuanyuan Zhou, Bokun Tian, Shunjun Wei, Xiaoling Zhang
Publikováno v:
IEEE Transactions on Instrumentation and Measurement. 72:1-12
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d2c0fb3dd080b1ab542c9864b30d49aa
https://doi.org/10.1109/tim.2023.3238757
https://doi.org/10.1109/tim.2023.3238757
Publikováno v:
Remote Sensing, Vol 13, Iss 21, p 4308 (2021)
Most of the existing image segmentation methods have a strong anti-noise ability but are susceptible to the interference in the background, so they are not suitable for 3-D synthetic aperture radar (SAR) image target extraction. Region of interest (R
Externí odkaz:
https://doaj.org/article/9bf5464f99e6439ea42b9f08d9a61d99
Publikováno v:
The Journal of Engineering (2019)
A novel method for synthetic aperture radar (SAR) three-dimensional (3D) sparse imaging based on a coprime linear array (CLA) is proposed. To reduce the geometric resolution loss caused by under-sampled sparse SAR, a jointed sparse imaging approach i
Externí odkaz:
https://doaj.org/article/ead4f6592f6e4edba36858ce61330096
Publikováno v:
Remote Sensing, Vol 13, Iss 9, p 1751 (2021)
Because of the three-dimensional (3D) imaging scene’s sparsity, compressed sensing (CS) algorithms can be used for linear array synthetic aperture radar (LASAR) 3D sparse imaging. CS algorithms usually achieve high-quality sparse imaging at the exp
Externí odkaz:
https://doaj.org/article/05b3cd0e4a614bf68c44c9ad4e4c9164
Publikováno v:
IEEE Antennas and Wireless Propagation Letters. 20:1537-1541
Sparse Bayesian (SB) 3-D imaging resolution transcends classical radar cross section (RCS) imaging, providing a novel solution for low-RCS objects. To better resolve low-RCS objects, we propose an improved SB 3-D imaging algorithm via dyadic Green's
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7c19f119b55a85ae5e2a550b87b3e76f
https://doi.org/10.1109/lawp.2021.3090052
https://doi.org/10.1109/lawp.2021.3090052