Sparse signal representation ISAR imaging method based on sparse bayesian learning

被引:0
|
作者
Cheng, Ping [1 ]
Si, Xi-Cai [1 ]
Jiang, Yi-Cheng [2 ]
Xu, Rong-Qing [2 ]
机构
[1] College of Information and Communication Engineering, Harbin Engineering University, Harbin 150001, China
[2] Research Institute of Electronic Engineering Technology, Harbin Institute of Technology, Harbin 150001, China
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关键词
Algorithms - Radar imaging;
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摘要
As a new sparse signal representation algorithm, SBL (sparse Bayesian learning) method has no structural error as BP and has much fewer local minima than FOCUSS. ISAR imaging problem can be transformed into a sparse signal representation problem, therefore in the paper SBL is first applied in ISAR imaging. Imaging results of real data show SBL is a more effective ISAR imaging algorithm than BP and FOCUSS.
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页码:547 / 550
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