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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Bibliographic Details
Published in:	2017 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC) pp. 1 - 4
Main Authors:	Chen Wen-feng, Chen Liang-dong, Lv Ming-jiu, Yang Jun, Ma Xiao-yan
Format:	Conference Proceeding
Language:	English
Published:	IEEE 01.10.2017
Subjects:	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
Online Access:	Get full text
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Summary:	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