Sub-Nyquist sampling and reconstruction model of LFM signals based on blind compressed sensing in FRFT domain

DOI10.1007/s00034-014-9859-5zbMath1401.94033OpenAlexW2086603923MaRDI QIDQ736382

Biao Fang, Jun Gao, Gaoming Huang

Publication date: 4 August 2016

Published in: Circuits, Systems, and Signal Processing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s00034-014-9859-5

zbMATH Keywords

blind compressed sensing (BCS)fractional Fourier transform (FRFT)linear frequency modulated (LFM)random demodulatorsub-Nyquist sampling

Mathematics Subject Classification ID

Signal theory (characterization, reconstruction, filtering, etc.) (94A12)

Cites Work

• Closed-form discrete fractional and affine Fourier transforms
• Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information
• The Fractional Order Fourier Transform and its Application to Quantum Mechanics
• Blind Multiband Signal Reconstruction: Compressed Sensing for Analog Signals
• Structured Compressed Sensing: From Theory to Applications
• Beyond Nyquist: Efficient Sampling of Sparse Bandlimited Signals
• Blind Compressed Sensing
• Sampling signals with finite rate of innovation
• Optimally sparse representation in general (nonorthogonal) dictionaries via ℓ ¹ minimization
• Compressed sensing

This page was built for publication: Sub-Nyquist sampling and reconstruction model of LFM signals based on blind compressed sensing in FRFT domain