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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Vydáno v:	2017 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC) s. 1 - 4
Hlavní autoři:	Chen Wen-feng, Chen Liang-dong, Lv Ming-jiu, Yang Jun, Ma Xiao-yan
Médium:	Konferenční příspěvek
Jazyk:	angličtina
Vydáno:	IEEE 01.10.2017
Témata:	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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Shrnutí:	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.
DOI:	10.1109/ICSPCC.2017.8242543