Sparse signal representation ISAR imaging method based on sparse bayesian learning

Ping Cheng; Xi Cai Si; Yi Cheng Jiang; Rong Qing Xu

Sparse signal representation ISAR imaging method based on sparse bayesian learning

Ping Cheng^*
, Xi Cai Si
, Yi Cheng Jiang
, Rong Qing Xu

^*Corresponding author for this work

School of Electronics and Information Engineering

College of Information and Communication Engineering, Harbin Engineering University
Harbin Institute of Technology

Research output: Contribution to journal › Article › peer-review

11 Scopus citations

Abstract

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.

Original language	English
Pages (from-to)	547-550
Number of pages	4
Journal	Tien Tzu Hsueh Pao/Acta Electronica Sinica
Volume	36
Issue number	3
State	Published - Mar 2008

Keywords

BP (Basis Pursuit)
Focal underdetermined system solver
ISAR (inverse synthetic aperture radar)
SBL (sparse Bayesian learning)
Sparse signal representation

Cite this

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title = "Sparse signal representation ISAR imaging method based on sparse bayesian learning",

abstract = "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.",

keywords = "BP (Basis Pursuit), Focal underdetermined system solver, ISAR (inverse synthetic aperture radar), SBL (sparse Bayesian learning), Sparse signal representation",

author = "Ping Cheng and Si, \{Xi Cai\} and Jiang, \{Yi Cheng\} and Xu, \{Rong Qing\}",

year = "2008",

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language = "英语",

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journal = "Tien Tzu Hsueh Pao/Acta Electronica Sinica",

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T1 - Sparse signal representation ISAR imaging method based on sparse bayesian learning

AU - Cheng, Ping

AU - Si, Xi Cai

AU - Jiang, Yi Cheng

AU - Xu, Rong Qing

PY - 2008/3

Y1 - 2008/3

N2 - 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.

AB - 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.

KW - BP (Basis Pursuit)

KW - Focal underdetermined system solver

KW - ISAR (inverse synthetic aperture radar)

KW - SBL (sparse Bayesian learning)

KW - Sparse signal representation

UR - https://www.scopus.com/pages/publications/43249090395

M3 - 文章

AN - SCOPUS:43249090395

SN - 0372-2112

VL - 36

SP - 547

EP - 550

JO - Tien Tzu Hsueh Pao/Acta Electronica Sinica

JF - Tien Tzu Hsueh Pao/Acta Electronica Sinica

IS - 3

ER -

Sparse signal representation ISAR imaging method based on sparse bayesian learning

Abstract

Keywords

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