Paper Info
Title
A modified sparse reconstruction method for three-dimensional synthetic aperture radar image.
Abstract
There is an increasing interest in three-dimensional Synthetic Aperture Radar (3-D SAR) imaging from observed sparse scattering data. However, the existing 3-D sparse imaging method requires large computing times and storage capacity. In this paper, we propose a modified method for the sparse 3-D SAR imaging. The method processes the collection of noisy SAR measurements, usually collected over nonlinear flight paths, and outputs 3-D SAR imagery. Firstly, the 3-D sparse reconstruction problem is transformed into a series of 2-D slices reconstruction problem by range compression. Then the slices are reconstructed by the modified SL0 (smoothed l(0) norm) reconstruction algorithm. The improved algorithm uses hyperbolic tangent function instead of the Gaussian function to approximate the l(0) norm and uses the Newton direction instead of the steepest descent direction, which can speed up the convergence rate of the SLO algorithm. Finally, numerical simulation results are given to demonstrate the effectiveness of the proposed algorithm. It is shown that our method, compared with existing 3-D sparse imaging method, performs better in reconstruction quality and the reconstruction time.
Year
DOI
Venue
2017
10.1117/12.2289440
Proceedings of SPIE
Keywords
Field
DocType
Synthetic Aperture Radar,three-dimensional imaging,sparse reconstruction,smoothed l(0) norm
Computer vision,Synthetic aperture radar image,Computer science,Artificial intelligence
Conference
Volume
ISSN
Citations 
10611
0277-786X
0
PageRank 
References 
Authors
0.34
0
4
Name
Order
Citations
PageRank
Ziqiang Zhang100.34
Kefeng Ji217617.01
Haibo Song300.34
Huanxin Zou418419.43