ISAR imaging via adaptive sparse recovery

Author

Wei Rao ; Gang Li ; Xiqin Wang

Author_Institution

Dept. of Electron. Eng., Tsinghua Univ., Beijing, China

fYear

2013

fDate

21-26 July 2013

Firstpage

121

Lastpage

124

Abstract

A novel high resolution ISAR imaging method based on adaptive sparse recovery is proposed in his paper. The ISAR signal in each range bin is sparsely represented by an over-complete chirplet basis matrix, which can be determined by an unknown parameter set. An adaptive parametric sparse recovery method is proposed to retrieve both the parameter set and the ISAR image. This goal is achieved by sequentially minimizing the L₁ norm of the sparse signal and the energy of the recovery error in an iterative manner.

Keywords

image representation; image resolution; image retrieval; iterative methods; minimisation; radar imaging; sparse matrices; synthetic aperture radar; ISAR imaging; ISAR signal; L₁ norm minimization; adaptive parametric sparse recovery method; chirplet basis matrix; image resolution; iterative method; sequential minimization; sparse representation; Algorithm design and analysis; Chirp; Estimation; Image resolution; Imaging; Signal resolution; Sparse matrices; ISAR imaging; adaptive sparse recovery; parametric sparse representation;

fLanguage

English

Publisher

ieee

Conference_Titel

Geoscience and Remote Sensing Symposium (IGARSS), 2013 IEEE International

Conference_Location

Melbourne, VIC

ISSN

2153-6996

Print_ISBN

978-1-4799-1114-1

Type

conf

DOI

10.1109/IGARSS.2013.6721107

Filename

6721107