ISAR Imaging Based on Multiple Measurement Vector Model Sparse Signal Recovery Algorithm
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...
Main Author: | Junjie Feng |
---|---|
Format: | Article |
Language: | English |
Published: |
Hindawi Limited
2020-01-01
|
Series: | Mathematical Problems in Engineering |
Online Access: | http://dx.doi.org/10.1155/2020/1743593 |
Similar Items
-
High-Resolution ISAR Imaging Based on Improved Sparse Signal Recovery Algorithm
by: Junjie Feng, et al.
Published: (2021-01-01) -
SA-ISAR imaging algorithm based on the gradient signal recovery method
by: Bingren Ji, et al.
Published: (2019-08-01) -
Sparse Recovery With Block Multiple Measurement Vectors Algorithm
by: Yanli Shi, et al.
Published: (2019-01-01) -
Sparse Aperture InISAR Imaging via Sequential Multiple Sparse Bayesian Learning
by: Shuanghui Zhang, et al.
Published: (2017-10-01) -
High-resolution Distributed ISAR Imaging based on Sparse Representation
by: Li Yuanyuan, et al.
Published: (2018-01-01)