Open AccessISAR Imaging Based on Block Sparse Smoothed L0 Norm Recovery Algorithm
Author(s) -
Jundong Feng,
Xuwen Zhang,
Yonghui Wang
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1213/3/032018
Subject(s) - inverse synthetic aperture radar , algorithm , gradient descent , computer science , norm (philosophy) , block (permutation group theory) , mathematical optimization , radar imaging , radar , mathematics , artificial intelligence , artificial neural network , telecommunications , geometry , political science , law
In order to obtain high resolution inverse synthetic aperture radar (ISAR) sparse images, a block sparse signal recovery ISAR imaging algorithm is proposed by considering the cluster characteristics of target in this paper. Firstly, the ISAR sparse imaging model is established, the imaging is converted to L0 norm optimization problem. Secondly, one negative exponential function sequence is used as smoothed function to approach the block L0 norm. Finally, the revised step is added to ensure solving the optimization problem along the steepest descent gradient direction and the cost function is updated for the next loop. Simulation results verify the proposed algorithm is effective.