ISAR Imaging Based on Multiple Measurement Vector Model Sparse Signal Recovery Algorithm
Author
Source
Mathematical Problems in Engineering
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-07-13
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Abstract EN
A multiple measurement vector (MMV) model blocks sparse signal recovery.
ISAR imaging algorithm is proposed to improve ISAR imaging quality.
Firstly, the sparse imaging model is built, and block sparse signal recovery algorithm-based MMV model is applied to ISAR imaging.
Then, a negative exponential function is proposed to approximately block L0 norm.
The optimization solution of smoothed function is obtained by constructing a decreasing sequence.
Finally, the correction steps are added to ensure the optimal solution of the block sparse signal along the fastest descent direction.
Several simulations and real data simulation experiments verify the proposed algorithm has advantages in imaging time and quality.
American Psychological Association (APA)
Feng, Junjie. 2020. ISAR Imaging Based on Multiple Measurement Vector Model Sparse Signal Recovery Algorithm. Mathematical Problems in Engineering،Vol. 2020, no. 2020, pp.1-8.
https://search.emarefa.net/detail/BIM-1193465
Modern Language Association (MLA)
Feng, Junjie. ISAR Imaging Based on Multiple Measurement Vector Model Sparse Signal Recovery Algorithm. Mathematical Problems in Engineering No. 2020 (2020), pp.1-8.
https://search.emarefa.net/detail/BIM-1193465
American Medical Association (AMA)
Feng, Junjie. ISAR Imaging Based on Multiple Measurement Vector Model Sparse Signal Recovery Algorithm. Mathematical Problems in Engineering. 2020. Vol. 2020, no. 2020, pp.1-8.
https://search.emarefa.net/detail/BIM-1193465
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1193465