Zobrazeno 1 - 10
of 49
pro vyhledávání: '"Shuanghui ZHANG"'
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 4936-4951 (2024)
Achieving automatic target recognition in synthetic aperture radar (SAR) imagery is a long-standing difficulty because of the limited training samples and its sensitivity to imaging condition. Active target recognition methods can offer an innovative
Externí odkaz:
https://doaj.org/article/329978ded55644de8072f5c343b1c0a8
Publikováno v:
Leida xuebao, Vol 12, Iss 4, Pp 849-859 (2023)
Sparse Aperture-Inverse Synthetic Aperture Radar (SA-ISAR) imaging methods aim to reconstruct high-quality ISAR images from the corresponding incomplete ISAR echoes. The existing SA-ISAR imaging methods can be roughly divided into two categories: mod
Externí odkaz:
https://doaj.org/article/a48ac149eb284751aec024fd93b6f5a7
Publikováno v:
Electronics Letters, Vol 59, Iss 1, Pp n/a-n/a (2023)
Abstract It is difficult to estimate the effective rotation velocity for non‐triaxial stabilized space targets, which leads to deviations in the estimation of imaging plane vectors and azimuth resolution. This makes it hard to reconstruct the three
Externí odkaz:
https://doaj.org/article/51bd503632cf406e8dee5023b44c1eca
Publikováno v:
Leida xuebao, Vol 10, Iss 3, Pp 416-431 (2021)
The disadvantages of the traditional Inverse Synthetic Aperture Radar (ISAR) imaging method based on Fourier transform include large data storage and long collection time. The Compressive Sensing (CS) theory can use limited data to restore an image w
Externí odkaz:
https://doaj.org/article/0dcd0d4b91d14758836a69f3d915ba43
Publikováno v:
IEEE Access, Vol 5, Pp 26690-26702 (2017)
This paper presents a new sparse signal recovery algorithm using variational Bayesian inference based on the Laplace approximation. The sparse signal is modeled as the Laplacian scale mixture (LSM) prior. The Bayesian inference with the Laplacian mod
Externí odkaz:
https://doaj.org/article/9fc56f30118a4fa287547e3049ab4ccd
Publikováno v:
Sensors, Vol 15, Iss 8, Pp 18402-18415 (2015)
In this paper, two novel speed compensation algorithms for ISAR imaging under a low signal-to-noise ratio (SNR) condition have been proposed, which are based on the cubic phase function (CPF) and the integrated cubic phase function (ICPF), respective
Externí odkaz:
https://doaj.org/article/13b8f0f93a0943fea2b01c842178fd99
Publikováno v:
Sensors, Vol 17, Iss 10, p 2295 (2017)
Interferometric inverse synthetic aperture radar (InISAR) imaging for sparse-aperture (SA) data is still a challenge, because the similarity and matched degree between ISAR images from different channels are destroyed by the SA data. To deal with thi
Externí odkaz:
https://doaj.org/article/b75dcc286dbf4474aab032c4c781ba0e
Publikováno v:
Sensors, Vol 16, Iss 5, p 611 (2016)
This paper presents a novel Inverse Synthetic Aperture Radar Imaging (ISAR) algorithm based on a new sparse prior, known as the logarithmic Laplacian prior. The newly proposed logarithmic Laplacian prior has a narrower main lobe with higher tail valu
Externí odkaz:
https://doaj.org/article/9b5a90b4bcc343c58ee2ea7bacf01f15
Publikováno v:
IEEE Transactions on Aerospace and Electronic Systems. :1-17
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::43f72cc3132749ddb436453ecc58459c
https://doi.org/10.1109/taes.2023.3273203
https://doi.org/10.1109/taes.2023.3273203
Publikováno v:
IEEE Wireless Communications Letters. 11:1895-1899
This letter proposes a learning aided gradient descent (LAGD) algorithm to solve the weighted sum rate (WSR) maximization problem for multiple-input single-output (MISO) beamforming. The proposed LAGD algorithm directly optimizes the transmit precode
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7011745e9f89b7a27ed5eee844ede971
https://doi.org/10.1109/lwc.2022.3186160
https://doi.org/10.1109/lwc.2022.3186160