Title :
ISAR imaging via adaptive sparse recovery
Author :
Wei Rao ; Gang Li ; Xiqin Wang
Author_Institution :
Dept. of Electron. Eng., Tsinghua Univ., Beijing, China
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;
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2013 IEEE International
Conference_Location :
Melbourne, VIC
Print_ISBN :
978-1-4799-1114-1
DOI :
10.1109/IGARSS.2013.6721107
