SAR Ground Moving Target Imaging Algorithm Based on Parametric and Dynamic Sparse Bayesian Learning

SAR Ground Moving Target Imaging Algorithm Based on Parametric and Dynamic Sparse Bayesian Learning

In this paper, a novel synthetic aperture radar (SAR) ground moving target imaging (GMTIm) algorithm is presented within a parametric and dynamic sparse Bayesian learning (SBL) framework. A new time-frequency representation, which is known as Lv's distribution (LVD), is employed on the moving t...

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Bibliographic Details
Main Authors: Yang, Lei, Zhao, Lifan, Bi, Guoan, Zhang, Liren
Other Authors: School of Electrical and Electronic Engineering
Format: Journal Article
Language:English
Published: 2017
Subjects:
Ground moving target imaging
Lv’s distribution
Online Access:https://hdl.handle.net/10356/86047
http://hdl.handle.net/10220/43922

Internet

https://hdl.handle.net/10356/86047
http://hdl.handle.net/10220/43922

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