@inproceedings{f167b0e2f9b54f6b9df27e8e9f75fc5a,
title = "A novel algorithm for synthetic aperture radar imaging based on compressed sensing",
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 = "Compressed sensing, Fractional Fourier transform, Synthetic aperture radar",
author = "Hongxia Bu and Xia Bai and Ran Tao",
year = "2010",
doi = "10.1109/ICOSP.2010.5656093",
language = "English",
isbn = "9781424458981",
series = "International Conference on Signal Processing Proceedings, ICSP",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "2210--2213",
booktitle = "ICSP2010 - 2010 IEEE 10th International Conference on Signal Processing, Proceedings",
address = "United States",
}