The paper discusses a novel frequency interpolation and super-resolution method for multitone waveform analysis, where a compressive sensing algorithm is employed to process data. Each signal acquisition involves a short data record, whose DFT coefficients are computed. A set of compressed measurements is obtained by taking records with different known starting instants, and employed to determine, by solving an orthogonal matching pursuit problem, the set of frequency components of the analysed waveform. Interpolation is presented as a compressed sensing problem and algorithm performances discussed.
On compressed sensing and super-resolution in DFT-based spectral analysis
BERTOCCO, MATTEO;FRIGO, GUGLIELMO;NARDUZZI, CLAUDIO
2013
Abstract
The paper discusses a novel frequency interpolation and super-resolution method for multitone waveform analysis, where a compressive sensing algorithm is employed to process data. Each signal acquisition involves a short data record, whose DFT coefficients are computed. A set of compressed measurements is obtained by taking records with different known starting instants, and employed to determine, by solving an orthogonal matching pursuit problem, the set of frequency components of the analysed waveform. Interpolation is presented as a compressed sensing problem and algorithm performances discussed.File in questo prodotto:
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