A novel algorithm for synthetic aperture radar imaging based on compressed sensing

Hongxia Bu, Xia Bai*, Ran Tao

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Citations (Scopus)

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.

Original languageEnglish
Title of host publicationICSP2010 - 2010 IEEE 10th International Conference on Signal Processing, Proceedings
Pages2210-2213
Number of pages4
DOIs
Publication statusPublished - 2010
Event2010 IEEE 10th International Conference on Signal Processing, ICSP2010 - Beijing, China
Duration: 24 Oct 201028 Oct 2010

Publication series

NameInternational Conference on Signal Processing Proceedings, ICSP

Conference

Conference2010 IEEE 10th International Conference on Signal Processing, ICSP2010
Country/TerritoryChina
CityBeijing
Period24/10/1028/10/10

Keywords

  • Compressed sensing
  • Fractional Fourier transform
  • Synthetic aperture radar

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