Title :
Structured sparse representation based ISAR imaging
Author :
Lu Wang ; Lifan Zhao ; Guoan Bi
Author_Institution :
Sch. of Electr. & Electron. Eng., Nanyang Technol. Univ., Singapore, Singapore
Abstract :
Inverse Synthetic Aperture Radar (ISAR) imaging based on sparse representation (SR) is well known for its advantages of achieving high resolution with limited measurements. This paper extends the SR based ISAR imaging to further include the continuity structures of the target scene. After range compression, two kinds of structured sparse recovery methods are performed in each range cell to encourage the continuities in cross-range and range, respectively, by clustering the scatterers with nonzero magnitudes. Both structured sparse representation based ISAR imaging methods achieve better target images in terms of removing the noise outside target region and preserving the weak target scatterers over the conventional SR based ISAR imaging methods.
Keywords :
radar imaging; synthetic aperture radar; ISAR imaging; inverse synthetic aperture radar imaging; range compression; structured sparse recovery methods; structured sparse representation based imaging; target scene; Bayes methods; Compressed sensing; Correlation; Doppler effect; Entropy; Imaging; Radar imaging; ISAR imaging; sparse representation; structural information;
Conference_Titel :
Radar Symposium (IRS), 2014 15th International
Conference_Location :
Gdansk
Print_ISBN :
978-617-607-552-3
DOI :
10.1109/IRS.2014.6869264