Iteratively reweighted complex approximate message passing for ISAR imaging with cluster sparse structure

An iteratively reweighted complex approximate message passing algorithm is proposed for cluster sparse inverse synthetic aperture radar imaging. The proposed algorithm improves the recovery performance of cluster sparse signal. A pattern-coupled weight update rule is introduced to establish a coupli...

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Veröffentlicht in:2017 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC) S. 1 - 4
Hauptverfasser: Chen Wen-feng, Chen Liang-dong, Lv Ming-jiu, Yang Jun, Ma Xiao-yan
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: IEEE 01.10.2017
Schlagworte:
Approximation algorithms
cluster sparse
Clustering algorithms
complex approximate message passing
Image reconstruction
Imaging
inverse synthetic aperture radar imaging
iteratively reweighted f 1 minimization
Message passing
Radar imaging
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Abstract An iteratively reweighted complex approximate message passing algorithm is proposed for cluster sparse inverse synthetic aperture radar imaging. The proposed algorithm improves the recovery performance of cluster sparse signal. A pattern-coupled weight update rule is introduced to establish a coupling relation between the sparsity patterns of neighboring coefficients. Real radar data results demonstrate the superior reconstruction performance in terms of reconstruction accuracy and computation time.
AbstractList An iteratively reweighted complex approximate message passing algorithm is proposed for cluster sparse inverse synthetic aperture radar imaging. The proposed algorithm improves the recovery performance of cluster sparse signal. A pattern-coupled weight update rule is introduced to establish a coupling relation between the sparsity patterns of neighboring coefficients. Real radar data results demonstrate the superior reconstruction performance in terms of reconstruction accuracy and computation time.
Author Chen Wen-feng
Chen Liang-dong
Lv Ming-jiu
Yang Jun
Ma Xiao-yan
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  surname: Chen Wen-feng
  fullname: Chen Wen-feng
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  organization: No. Three Dept., Air Force Early Warning Acad., Wuhan, China
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  surname: Chen Liang-dong
  fullname: Chen Liang-dong
  email: 13476810127@126.com
  organization: No. Three Dept., Air Force Early Warning Acad., Wuhan, China
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  surname: Lv Ming-jiu
  fullname: Lv Ming-jiu
  email: lv_mingjiu@163.com
  organization: No. Three Dept., Air Force Early Warning Acad., Wuhan, China
– sequence: 4
  surname: Yang Jun
  fullname: Yang Jun
  email: yangjem@126.com
  organization: No. Three Dept., Air Force Early Warning Acad., Wuhan, China
– sequence: 5
  surname: Ma Xiao-yan
  fullname: Ma Xiao-yan
  email: ma_x_yan@163.com
  organization: No. Three Dept., Air Force Early Warning Acad., Wuhan, China
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Snippet An iteratively reweighted complex approximate message passing algorithm is proposed for cluster sparse inverse synthetic aperture radar imaging. The proposed...
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SubjectTerms Approximation algorithms
cluster sparse
Clustering algorithms
complex approximate message passing
Image reconstruction
Imaging
inverse synthetic aperture radar imaging
iteratively reweighted f 1 minimization
Message passing
Radar imaging
Title Iteratively reweighted complex approximate message passing for ISAR imaging with cluster sparse structure
URI https://ieeexplore.ieee.org/document/8242543
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