Sensors | |
Bayesian Deconvolution for Angular Super-Resolution in Forward-Looking Scanning Radar | |
Yuebo Zha1  Yulin Huang2  Zhichao Sun2  Yue Wang2  Jianyu Yang2  | |
[1] School of Electronic Engineering, University of Electronic Science and Technology of China, 2006 Xiyuan Road, Gaoxin Western District, Chengdu 611731, China; | |
关键词: deconvolution; Bayesian; radar imaging; super-resolution; convex optimization; | |
DOI : 10.3390/s150306924 | |
来源: mdpi | |
【 摘 要 】
Scanning radar is of notable importance for ground surveillance, terrain mapping and disaster rescue. However, the angular resolution of a scanning radar image is poor compared to the achievable range resolution. This paper presents a deconvolution algorithm for angular super-resolution in scanning radar based on Bayesian theory, which states that the angular super-resolution can be realized by solving the corresponding deconvolution problem with the maximum a
【 授权许可】
CC BY
© 2015 by the authors; licensee MDPI, Basel, Switzerland.
【 预 览 】
Files | Size | Format | View |
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RO202003190014861ZK.pdf | 7663KB | download |