Title :
A novel algorithm for synthetic aperture radar imaging based on compressed sensing
Author :
Bu, Hongxia ; Bai, Xia ; Tao, Ran
Author_Institution :
Dept. of Electron. Eng., Beijing Inst. of Technol., Beijing, China
Abstract :
To achieve high-resolution images, synthetic aperture radar (SAR) faces considerable technical challenges such as huge amount of data samples and high hardware complexity. Compressed sensing (CS) theory shows that the super-resolved images can be reconstructed from an extremely smaller set of measurements than what is generally considered necessary by Nyquist/Shannon theorem. In this paper, a new algorithm of SAR imaging based on the concept of CS is presented, in which a random fractional Fourier transform (FRFT) matrix is used as the sensing matrix. By utilizing the FRFT matrix the demodulator for de-ramping the linear frequency modulation signal can be eliminated. Simulation results with both simulated and real data exhibit the validity of the proposed algorithm.
Keywords :
Fourier transforms; demodulators; frequency modulation; image reconstruction; image resolution; matrix algebra; radar imaging; synthetic aperture radar; FRFT matrix; Nyquist-Shannon theorem; SAR imaging; compressed sensing theory; demodulator; high hardware complexity; high resolution image; linear frequency modulation signal deramping; random fractional Fourier transform matrix; sensing matrix; super resolved image reconstruction; synthetic aperture radar imaging; Azimuth; Compressed sensing; Fourier transforms; Matching pursuit algorithms; Radar polarimetry; Sensors; Synthetic aperture radar; Compressed Sensing; Fractional Fourier Transform; Synthetic Aperture Radar;
Conference_Titel :
Signal Processing (ICSP), 2010 IEEE 10th International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-5897-4
DOI :
10.1109/ICOSP.2010.5656093